Overview

Dataset statistics

Number of variables30
Number of observations2083363
Missing cells3373
Missing cells (%)< 0.1%
Duplicate rows174167
Duplicate rows (%)8.4%
Total size in memory476.8 MiB
Average record size in memory240.0 B

Variable types

Categorical24
Numeric6

Warnings

modalidade_de_apoio has constant value "REEMBOLSÁVEL" Constant
forma_de_apoio has constant value "INDIRETA" Constant
Dataset has 174167 (8.4%) duplicate rows Duplicates
cliente has a high cardinality: 397313 distinct values High cardinality
cpf_cnpj has a high cardinality: 98152 distinct values High cardinality
municipio has a high cardinality: 5140 distinct values High cardinality
data_da_contratacao has a high cardinality: 5528 distinct values High cardinality
instrumento_financeiro has a high cardinality: 80 distinct values High cardinality
subsetor_cnae_codigo has a high cardinality: 1640 distinct values High cardinality
subsetor_cnae_nome has a high cardinality: 1604 distinct values High cardinality
instituicao_financeira_credenciada has a high cardinality: 127 distinct values High cardinality
cnpj_do_agente_financeiro has a high cardinality: 127 distinct values High cardinality
valor_da_operacao_em_reais is highly correlated with valor_desembolsado_reaisHigh correlation
valor_desembolsado_reais is highly correlated with valor_da_operacao_em_reaisHigh correlation
custo_financeiro is highly correlated with modalidade_de_apoio and 1 other fieldsHigh correlation
subsetor_cnae_agrupado is highly correlated with setor_cnae and 4 other fieldsHigh correlation
uf is highly correlated with modalidade_de_apoio and 1 other fieldsHigh correlation
area_operacional is highly correlated with modalidade_de_apoio and 1 other fieldsHigh correlation
setor_cnae is highly correlated with subsetor_cnae_agrupado and 3 other fieldsHigh correlation
subsetor_bndes is highly correlated with subsetor_cnae_agrupado and 4 other fieldsHigh correlation
porte_do_cliente is highly correlated with modalidade_de_apoio and 1 other fieldsHigh correlation
inovacao is highly correlated with modalidade_de_apoio and 1 other fieldsHigh correlation
modalidade_de_apoio is highly correlated with custo_financeiro and 14 other fieldsHigh correlation
instrumento_financeiro is highly correlated with modalidade_de_apoio and 1 other fieldsHigh correlation
forma_de_apoio is highly correlated with custo_financeiro and 14 other fieldsHigh correlation
setor_bndes is highly correlated with subsetor_cnae_agrupado and 3 other fieldsHigh correlation
fonte_de_recurso_desembolsos is highly correlated with modalidade_de_apoio and 1 other fieldsHigh correlation
produto is highly correlated with modalidade_de_apoio and 1 other fieldsHigh correlation
situacao_da_operacao is highly correlated with modalidade_de_apoio and 1 other fieldsHigh correlation
natureza_do_cliente is highly correlated with modalidade_de_apoio and 1 other fieldsHigh correlation
valor_da_operacao_em_reais is highly skewed (γ1 = 253.0599823) Skewed
valor_desembolsado_reais is highly skewed (γ1 = 256.9119925) Skewed
prazo_carencia_meses has 309940 (14.9%) zeros Zeros

Reproduction

Analysis started2021-08-19 01:45:21.701450
Analysis finished2021-08-19 02:27:54.588715
Duration42 minutes and 32.89 seconds
Software versionpandas-profiling v2.10.0
Download configurationconfig.yaml

Variables

cliente
Categorical

HIGH CARDINALITY

Distinct397313
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
BANCO DO BRASIL SA
 
87942
BANCO COOPERATIVO SICREDI S.A.
 
42745
BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL
 
39286
COOPERATIVA CENTRAL DE CREDITO RURAL COM INT (01401771)
 
32178
BANCO DO ESTADO DO RIO GRANDE DO SUL SA
 
24866
Other values (397308)
1856346 

Length

Max length55
Median length30
Mean length31.99611158
Min length3

Characters and Unicode

Total characters66659515
Distinct characters80
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193235 ?
Unique (%)9.3%

Sample

1st rowBANCO COOPERATIVO SICOOB S.A.
2nd rowBANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL
3rd rowBANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL
4th rowBANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL
5th rowBANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL
ValueCountFrequency (%)
BANCO DO BRASIL SA87942
 
4.2%
BANCO COOPERATIVO SICREDI S.A.42745
 
2.1%
BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL39286
 
1.9%
COOPERATIVA CENTRAL DE CREDITO RURAL COM INT (01401771)32178
 
1.5%
BANCO DO ESTADO DO RIO GRANDE DO SUL SA24866
 
1.2%
BANCO BRADESCO S.A.18265
 
0.9%
BANCO DE DESENVOLVIMENTO DO ESPIRITO SANTO S/A16849
 
0.8%
INDUSTRIAS ROMI S A14754
 
0.7%
COOPERATIVA CENTRAL DE CREDITO RURAL COM INTERACAO SOLI14035
 
0.7%
BANCO SANTANDER (BRASIL) S.A.12442
 
0.6%
Other values (397303)1780001
85.4%
2021-08-18T23:27:58.900420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ltda1239113
 
11.8%
de559896
 
5.3%
e454301
 
4.3%
me274516
 
2.6%
transportes271098
 
2.6%
264949
 
2.5%
do258251
 
2.5%
banco256112
 
2.4%
comercio176286
 
1.7%
s.a143335
 
1.4%
Other values (161478)6586224
62.8%

Most occurring characters

ValueCountFrequency (%)
8534230
12.8%
A7651860
11.5%
E5549057
 
8.3%
O5281545
 
7.9%
R4727129
 
7.1%
T4328709
 
6.5%
S4145484
 
6.2%
I4128240
 
6.2%
D3454519
 
5.2%
L3186999
 
4.8%
Other values (70)15671743
23.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter56650708
85.0%
Space Separator8534230
 
12.8%
Other Punctuation711841
 
1.1%
Decimal Number426992
 
0.6%
Dash Punctuation230696
 
0.3%
Open Punctuation52187
 
0.1%
Close Punctuation52186
 
0.1%
Math Symbol242
 
< 0.1%
Modifier Symbol151
 
< 0.1%
Lowercase Letter130
 
< 0.1%
Other values (5)152
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
A7651860
13.5%
E5549057
9.8%
O5281545
9.3%
R4727129
8.3%
T4328709
 
7.6%
S4145484
 
7.3%
I4128240
 
7.3%
D3454519
 
6.1%
L3186999
 
5.6%
C2897057
 
5.1%
Other values (18)11300109
19.9%
ValueCountFrequency (%)
.489366
68.7%
/112972
 
15.9%
&79893
 
11.2%
,25700
 
3.6%
'2596
 
0.4%
?539
 
0.1%
%515
 
0.1%
:100
 
< 0.1%
"60
 
< 0.1%
!35
 
< 0.1%
Other values (4)65
 
< 0.1%
ValueCountFrequency (%)
á32
24.6%
ç28
21.5%
a25
19.2%
é24
18.5%
o6
 
4.6%
í5
 
3.8%
ô4
 
3.1%
e2
 
1.5%
û2
 
1.5%
s1
 
0.8%
ValueCountFrequency (%)
1113794
26.7%
093592
21.9%
780649
18.9%
446230
10.8%
219147
 
4.5%
916079
 
3.8%
315656
 
3.7%
814408
 
3.4%
613791
 
3.2%
513646
 
3.2%
ValueCountFrequency (%)
+200
82.6%
=32
 
13.2%
~7
 
2.9%
¬3
 
1.2%
ValueCountFrequency (%)
(52186
> 99.9%
[1
 
< 0.1%
ValueCountFrequency (%)
)52185
> 99.9%
]1
 
< 0.1%
ValueCountFrequency (%)
16
72.7%
6
 
27.3%
ValueCountFrequency (%)
8534230
100.0%
ValueCountFrequency (%)
-230696
100.0%
ValueCountFrequency (%)
º50
100.0%
ValueCountFrequency (%)
¦57
100.0%
ValueCountFrequency (%)
_18
100.0%
ValueCountFrequency (%)
`151
100.0%
ValueCountFrequency (%)
$5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin56650888
85.0%
Common10008627
 
15.0%

Most frequent character per script

ValueCountFrequency (%)
A7651860
13.5%
E5549057
9.8%
O5281545
9.3%
R4727129
8.3%
T4328709
 
7.6%
S4145484
 
7.3%
I4128240
 
7.3%
D3454519
 
6.1%
L3186999
 
5.6%
C2897057
 
5.1%
Other values (30)11300289
19.9%
ValueCountFrequency (%)
8534230
85.3%
.489366
 
4.9%
-230696
 
2.3%
1113794
 
1.1%
/112972
 
1.1%
093592
 
0.9%
780649
 
0.8%
&79893
 
0.8%
(52186
 
0.5%
)52185
 
0.5%
Other values (30)169064
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII66658874
> 99.9%
None641
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
8534230
12.8%
A7651860
11.5%
E5549057
 
8.3%
O5281545
 
7.9%
R4727129
 
7.1%
T4328709
 
6.5%
S4145484
 
6.2%
I4128240
 
6.2%
D3454519
 
5.2%
L3186999
 
4.8%
Other values (57)15671102
23.5%
ValueCountFrequency (%)
Ç403
62.9%
¦57
 
8.9%
º50
 
7.8%
á32
 
5.0%
ç28
 
4.4%
é24
 
3.7%
¡22
 
3.4%
É10
 
1.6%
í5
 
0.8%
ô4
 
0.6%
Other values (3)6
 
0.9%

cpf_cnpj
Categorical

HIGH CARDINALITY

Distinct98152
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
**.*00.000/0001-**
 
87954
**.*81.521/0001-**
 
42746
**.*16.560/0001-**
 
39319
**.*01.771/0001-**
 
32188
**.*02.067/0001-**
 
24879
Other values (98147)
1856277 

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters37500534
Distinct characters14
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3573 ?
Unique (%)0.2%

Sample

1st row**.*38.232/0001-**
2nd row**.*16.560/0001-**
3rd row**.*16.560/0001-**
4th row**.*16.560/0001-**
5th row**.*16.560/0001-**
ValueCountFrequency (%)
**.*00.000/0001-**87954
 
4.2%
**.*81.521/0001-**42746
 
2.1%
**.*16.560/0001-**39319
 
1.9%
**.*01.771/0001-**32188
 
1.5%
**.*02.067/0001-**24879
 
1.2%
**.*46.948/0001-**18279
 
0.9%
**.*45.829/0001-**16858
 
0.8%
**.*20.428/0001-**14755
 
0.7%
**.*02.627/0001-**14060
 
0.7%
**.*00.888/0001-**12450
 
0.6%
Other values (98142)1779875
85.4%
2021-08-18T23:28:00.460799image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00.000/000187954
 
4.2%
81.521/000142746
 
2.1%
16.560/000139319
 
1.9%
01.771/000132188
 
1.5%
02.067/000124879
 
1.2%
46.948/000118279
 
0.9%
45.829/000116858
 
0.8%
20.428/000114755
 
0.7%
02.627/000114060
 
0.7%
00.888/000112450
 
0.6%
Other values (98142)1779875
85.4%

Most occurring characters

ValueCountFrequency (%)
*10416815
27.8%
07758109
20.7%
.4166726
 
11.1%
13154875
 
8.4%
/2083363
 
5.6%
-2083363
 
5.6%
21043055
 
2.8%
81033216
 
2.8%
61000455
 
2.7%
5992650
 
2.6%
Other values (4)3767907
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number18750267
50.0%
Other Punctuation16666904
44.4%
Dash Punctuation2083363
 
5.6%

Most frequent character per category

ValueCountFrequency (%)
07758109
41.4%
13154875
16.8%
21043055
 
5.6%
81033216
 
5.5%
61000455
 
5.3%
5992650
 
5.3%
7979515
 
5.2%
4959005
 
5.1%
3918769
 
4.9%
9910618
 
4.9%
ValueCountFrequency (%)
*10416815
62.5%
.4166726
 
25.0%
/2083363
 
12.5%
ValueCountFrequency (%)
-2083363
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common37500534
100.0%

Most frequent character per script

ValueCountFrequency (%)
*10416815
27.8%
07758109
20.7%
.4166726
 
11.1%
13154875
 
8.4%
/2083363
 
5.6%
-2083363
 
5.6%
21043055
 
2.8%
81033216
 
2.8%
61000455
 
2.7%
5992650
 
2.6%
Other values (4)3767907
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII37500534
100.0%

Most frequent character per block

ValueCountFrequency (%)
*10416815
27.8%
07758109
20.7%
.4166726
 
11.1%
13154875
 
8.4%
/2083363
 
5.6%
-2083363
 
5.6%
21043055
 
2.8%
81033216
 
2.8%
61000455
 
2.7%
5992650
 
2.6%
Other values (4)3767907
 
10.0%

uf
Categorical

HIGH CORRELATION

Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
SP
434734 
RS
288488 
PR
275219 
MG
232436 
SC
216139 
Other values (22)
636347 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6250089
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row SP
2nd row RS
3rd row RS
4th row RS
5th row RS
ValueCountFrequency (%)
SP434734
20.9%
RS288488
13.8%
PR275219
13.2%
MG232436
11.2%
SC216139
10.4%
RJ79365
 
3.8%
GO73032
 
3.5%
BA72898
 
3.5%
ES62616
 
3.0%
MT53894
 
2.6%
Other values (17)294542
14.1%
2021-08-18T23:28:01.213502image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sp434734
20.9%
rs288488
13.8%
pr275219
13.2%
mg232436
11.2%
sc216139
10.4%
rj79365
 
3.8%
go73032
 
3.5%
ba72898
 
3.5%
es62616
 
3.0%
mt53894
 
2.6%
Other values (17)294542
14.1%

Most occurring characters

ValueCountFrequency (%)
2083363
33.3%
S1042852
16.7%
P814644
 
13.0%
R679619
 
10.9%
M354473
 
5.7%
G305468
 
4.9%
C253913
 
4.1%
A155054
 
2.5%
E154206
 
2.5%
O109065
 
1.7%
Other values (8)297432
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter4166726
66.7%
Space Separator2083363
33.3%

Most frequent character per category

ValueCountFrequency (%)
S1042852
25.0%
P814644
19.6%
R679619
16.3%
M354473
 
8.5%
G305468
 
7.3%
C253913
 
6.1%
A155054
 
3.7%
E154206
 
3.7%
O109065
 
2.6%
B86104
 
2.1%
Other values (7)211328
 
5.1%
ValueCountFrequency (%)
2083363
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4166726
66.7%
Common2083363
33.3%

Most frequent character per script

ValueCountFrequency (%)
S1042852
25.0%
P814644
19.6%
R679619
16.3%
M354473
 
8.5%
G305468
 
7.3%
C253913
 
6.1%
A155054
 
3.7%
E154206
 
3.7%
O109065
 
2.6%
B86104
 
2.1%
Other values (7)211328
 
5.1%
ValueCountFrequency (%)
2083363
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6250089
100.0%

Most frequent character per block

ValueCountFrequency (%)
2083363
33.3%
S1042852
16.7%
P814644
 
13.0%
R679619
 
10.9%
M354473
 
5.7%
G305468
 
4.9%
C253913
 
4.1%
A155054
 
2.5%
E154206
 
2.5%
O109065
 
1.7%
Other values (8)297432
 
4.8%

municipio
Categorical

HIGH CARDINALITY

Distinct5140
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
SAO PAULO
 
72463
BELO HORIZONTE
 
32333
CURITIBA
 
31242
RIO DE JANEIRO
 
27641
GOIANIA
 
16161
Other values (5135)
1903523 

Length

Max length32
Median length9
Mean length10.50826764
Min length3

Characters and Unicode

Total characters21892536
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)< 0.1%

Sample

1st rowPEDREGULHO
2nd rowTRES DE MAIO
3rd rowERECHIM
4th rowERECHIM
5th rowHUMAITA
ValueCountFrequency (%)
SAO PAULO72463
 
3.5%
BELO HORIZONTE32333
 
1.6%
CURITIBA31242
 
1.5%
RIO DE JANEIRO27641
 
1.3%
GOIANIA16161
 
0.8%
MARINGA15910
 
0.8%
FORTALEZA15455
 
0.7%
RECIFE15342
 
0.7%
PORTO ALEGRE14995
 
0.7%
SALVADOR14552
 
0.7%
Other values (5130)1827269
87.7%
2021-08-18T23:28:01.915783image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sao192539
 
5.5%
do167345
 
4.8%
de98125
 
2.8%
rio74271
 
2.1%
paulo74169
 
2.1%
sul63163
 
1.8%
santa37591
 
1.1%
nova35451
 
1.0%
campo35153
 
1.0%
belo34540
 
1.0%
Other values (3865)2661033
76.6%

Most occurring characters

ValueCountFrequency (%)
A3635252
16.6%
O2280591
10.4%
I1717815
 
7.8%
R1682212
 
7.7%
E1448435
 
6.6%
1390017
 
6.3%
S1268368
 
5.8%
N1117875
 
5.1%
U881837
 
4.0%
T839433
 
3.8%
Other values (19)5630701
25.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter20480314
93.5%
Space Separator1390017
 
6.3%
Other Punctuation11469
 
0.1%
Dash Punctuation10736
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
A3635252
17.7%
O2280591
11.1%
I1717815
 
8.4%
R1682212
 
8.2%
E1448435
 
7.1%
S1268368
 
6.2%
N1117875
 
5.5%
U881837
 
4.3%
T839433
 
4.1%
L836799
 
4.1%
Other values (16)4771697
23.3%
ValueCountFrequency (%)
1390017
100.0%
ValueCountFrequency (%)
-10736
100.0%
ValueCountFrequency (%)
'11469
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin20480314
93.5%
Common1412222
 
6.5%

Most frequent character per script

ValueCountFrequency (%)
A3635252
17.7%
O2280591
11.1%
I1717815
 
8.4%
R1682212
 
8.2%
E1448435
 
7.1%
S1268368
 
6.2%
N1117875
 
5.5%
U881837
 
4.3%
T839433
 
4.1%
L836799
 
4.1%
Other values (16)4771697
23.3%
ValueCountFrequency (%)
1390017
98.4%
'11469
 
0.8%
-10736
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII21892536
100.0%

Most frequent character per block

ValueCountFrequency (%)
A3635252
16.6%
O2280591
10.4%
I1717815
 
7.8%
R1682212
 
7.7%
E1448435
 
6.6%
1390017
 
6.3%
S1268368
 
5.8%
N1117875
 
5.1%
U881837
 
4.0%
T839433
 
3.8%
Other values (19)5630701
25.7%

municipio_codigo
Real number (ℝ≥0)

Distinct5418
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3664379.874
Minimum0
Maximum9999999
Zeros26
Zeros (%)< 0.1%
Memory size15.9 MiB
2021-08-18T23:28:02.419775image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2111300
Q13167004
median3550308
Q34213609
95-th percentile5107602
Maximum9999999
Range9999999
Interquartile range (IQR)1046605

Descriptive statistics

Standard deviation838415.3134
Coefficient of variation (CV)0.2288014186
Kurtosis0.9026096602
Mean3664379.874
Median Absolute Deviation (MAD)573500
Skewness-0.5651104449
Sum7.634233447 × 1012
Variance7.029402377 × 1011
MonotocityNot monotonic
2021-08-18T23:28:02.736007image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
355030872463
 
3.5%
310620032333
 
1.6%
410690231242
 
1.5%
330455727641
 
1.3%
520870716161
 
0.8%
411520015910
 
0.8%
230440015455
 
0.7%
261160615342
 
0.7%
431490214995
 
0.7%
292740814552
 
0.7%
Other values (5408)1827269
87.7%
ValueCountFrequency (%)
026
 
< 0.1%
1100015228
 
< 0.1%
11000231570
0.1%
110003117
 
< 0.1%
1100049956
< 0.1%
ValueCountFrequency (%)
9999999122
 
< 0.1%
530010814454
0.7%
522230234
 
< 0.1%
522220330
 
< 0.1%
5222054401
 
< 0.1%

data_da_contratacao
Categorical

HIGH CARDINALITY

Distinct5528
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
2004-06-30
 
8281
2013-12-27
 
5280
2013-12-30
 
5051
2012-12-17
 
4478
2005-06-20
 
4341
Other values (5523)
2055932 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters20833630
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique293 ?
Unique (%)< 0.1%

Sample

1st row2002-01-02
2nd row2002-01-02
3rd row2002-01-02
4th row2002-01-02
5th row2002-01-02
ValueCountFrequency (%)
2004-06-308281
 
0.4%
2013-12-275280
 
0.3%
2013-12-305051
 
0.2%
2012-12-174478
 
0.2%
2005-06-204341
 
0.2%
2010-03-124063
 
0.2%
2010-06-023848
 
0.2%
2005-06-303778
 
0.2%
2011-10-193730
 
0.2%
2013-11-063633
 
0.2%
Other values (5518)2036880
97.8%
2021-08-18T23:28:03.636727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2004-06-308281
 
0.4%
2013-12-275280
 
0.3%
2013-12-305051
 
0.2%
2012-12-174478
 
0.2%
2005-06-204341
 
0.2%
2010-03-124063
 
0.2%
2010-06-023848
 
0.2%
2005-06-303778
 
0.2%
2011-10-193730
 
0.2%
2013-11-063633
 
0.2%
Other values (5518)2036880
97.8%

Most occurring characters

ValueCountFrequency (%)
05529049
26.5%
-4166726
20.0%
23643291
17.5%
13412098
16.4%
3723404
 
3.5%
4627673
 
3.0%
5569495
 
2.7%
6560446
 
2.7%
9550369
 
2.6%
8527330
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number16666904
80.0%
Dash Punctuation4166726
 
20.0%

Most frequent character per category

ValueCountFrequency (%)
05529049
33.2%
23643291
21.9%
13412098
20.5%
3723404
 
4.3%
4627673
 
3.8%
5569495
 
3.4%
6560446
 
3.4%
9550369
 
3.3%
8527330
 
3.2%
7523749
 
3.1%
ValueCountFrequency (%)
-4166726
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common20833630
100.0%

Most frequent character per script

ValueCountFrequency (%)
05529049
26.5%
-4166726
20.0%
23643291
17.5%
13412098
16.4%
3723404
 
3.5%
4627673
 
3.0%
5569495
 
2.7%
6560446
 
2.7%
9550369
 
2.6%
8527330
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII20833630
100.0%

Most frequent character per block

ValueCountFrequency (%)
05529049
26.5%
-4166726
20.0%
23643291
17.5%
13412098
16.4%
3723404
 
3.5%
4627673
 
3.0%
5569495
 
2.7%
6560446
 
2.7%
9550369
 
2.6%
8527330
 
2.5%

valor_da_operacao_em_reais
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED

Distinct226554
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean273316.6764
Minimum8
Maximum1000000000
Zeros0
Zeros (%)0.0%
Memory size15.9 MiB
2021-08-18T23:28:04.448706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile5160
Q141785
median112500
Q3233000
95-th percentile857500
Maximum1000000000
Range999999992
Interquartile range (IQR)191215

Descriptive statistics

Standard deviation1671683.305
Coefficient of variation (CV)6.116287255
Kurtosis108744.3808
Mean273316.6764
Median Absolute Deviation (MAD)84830
Skewness253.0599823
Sum5.69417851 × 1011
Variance2.794525072 × 1012
MonotocityNot monotonic
2021-08-18T23:28:05.024924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000023593
 
1.1%
1000022497
 
1.1%
20000021403
 
1.0%
500014706
 
0.7%
5000014229
 
0.7%
15000012592
 
0.6%
1800010700
 
0.5%
300009972
 
0.5%
40009939
 
0.5%
60009812
 
0.5%
Other values (226544)1933920
92.8%
ValueCountFrequency (%)
81
< 0.1%
102
< 0.1%
181
< 0.1%
311
< 0.1%
401
< 0.1%
ValueCountFrequency (%)
10000000001
< 0.1%
7149383131
< 0.1%
6015442841
< 0.1%
6000000001
< 0.1%
5000000002
< 0.1%

valor_desembolsado_reais
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED

Distinct229424
Distinct (%)11.0%
Missing2937
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean268115.0582
Minimum8
Maximum999999999
Zeros0
Zeros (%)0.0%
Memory size15.9 MiB
2021-08-18T23:28:05.719239image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile5130
Q141590
median112400
Q3232000
95-th percentile843734.5
Maximum999999999
Range999999991
Interquartile range (IQR)190410

Descriptive statistics

Standard deviation1594244.404
Coefficient of variation (CV)5.946120353
Kurtosis115126.2986
Mean268115.0582
Median Absolute Deviation (MAD)84600
Skewness256.9119925
Sum5.577935381 × 1011
Variance2.541615221 × 1012
MonotocityNot monotonic
2021-08-18T23:28:06.099936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000023570
 
1.1%
1000022479
 
1.1%
20000021342
 
1.0%
500014703
 
0.7%
5000014188
 
0.7%
15000012532
 
0.6%
1800010696
 
0.5%
300009945
 
0.5%
40009937
 
0.5%
60009811
 
0.5%
Other values (229414)1931223
92.7%
ValueCountFrequency (%)
81
< 0.1%
102
< 0.1%
181
< 0.1%
311
< 0.1%
401
< 0.1%
ValueCountFrequency (%)
9999999991
< 0.1%
6015442841
< 0.1%
6000000001
< 0.1%
5000000002
< 0.1%
4812022021
< 0.1%

fonte_de_recurso_desembolsos
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
RECURSOS LIVRES - TESOURO
1235930 
RECURSOS LIVRES - PRÓPRIOS
379277 
RECURSOS LIVRES - FAT
237389 
RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAIS
176571 
RECURSOS LIVRES - ORGANISMOS
 
36017
Other values (4)
 
18179

Length

Max length45
Median length25
Mean length26.48261825
Min length1

Characters and Unicode

Total characters55172907
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRECURSOS LIVRES - TESOURO
2nd rowRECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAIS
3rd rowRECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAIS
4th rowRECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAIS
5th rowRECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAIS
ValueCountFrequency (%)
RECURSOS LIVRES - TESOURO1235930
59.3%
RECURSOS LIVRES - PRÓPRIOS379277
 
18.2%
RECURSOS LIVRES - FAT237389
 
11.4%
RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAIS176571
 
8.5%
RECURSOS LIVRES - ORGANISMOS36017
 
1.7%
RECURSOS VINCULADOS - PIS/PASEP14794
 
0.7%
-2937
 
0.1%
RECURSOS VINCULADOS - FUNDO CLIMA263
 
< 0.1%
RECURSOS LIVRES - FND185
 
< 0.1%
2021-08-18T23:28:06.707802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-08-18T23:28:06.974557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
2083363
24.0%
recursos2080426
24.0%
livres1888798
21.8%
tesouro1235930
14.2%
fat413960
 
4.8%
próprios379277
 
4.4%
vinculados191628
 
2.2%
especiais176571
 
2.0%
depósitos176571
 
2.0%
organismos36017
 
0.4%
Other values (4)15505
 
0.2%

Most occurring characters

ValueCountFrequency (%)
S8664391
15.7%
R8080151
14.6%
6594683
12.0%
E5749661
10.4%
O5372059
9.7%
U3508247
6.4%
I3040490
 
5.5%
C2448888
 
4.4%
-2083363
 
3.8%
L2080689
 
3.8%
Other values (11)7550285
13.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter46480067
84.2%
Space Separator6594683
 
12.0%
Dash Punctuation2083363
 
3.8%
Other Punctuation14794
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
S8664391
18.6%
R8080151
17.4%
E5749661
12.4%
O5372059
11.6%
U3508247
7.5%
I3040490
 
6.5%
C2448888
 
5.3%
L2080689
 
4.5%
V2080426
 
4.5%
T1826461
 
3.9%
Other values (8)3628604
7.8%
ValueCountFrequency (%)
6594683
100.0%
ValueCountFrequency (%)
-2083363
100.0%
ValueCountFrequency (%)
/14794
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin46480067
84.2%
Common8692840
 
15.8%

Most frequent character per script

ValueCountFrequency (%)
S8664391
18.6%
R8080151
17.4%
E5749661
12.4%
O5372059
11.6%
U3508247
7.5%
I3040490
 
6.5%
C2448888
 
5.3%
L2080689
 
4.5%
V2080426
 
4.5%
T1826461
 
3.9%
Other values (8)3628604
7.8%
ValueCountFrequency (%)
6594683
75.9%
-2083363
 
24.0%
/14794
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII54617059
99.0%
None555848
 
1.0%

Most frequent character per block

ValueCountFrequency (%)
S8664391
15.9%
R8080151
14.8%
6594683
12.1%
E5749661
10.5%
O5372059
9.8%
U3508247
6.4%
I3040490
 
5.6%
C2448888
 
4.5%
-2083363
 
3.8%
L2080689
 
3.8%
Other values (10)6994437
12.8%
ValueCountFrequency (%)
Ó555848
100.0%

custo_financeiro
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
TAXA FIXA
1215892 
TJLP
563382 
TJ462
159600 
TLP
 
79331
SELIC
 
56629
Other values (6)
 
8529

Length

Max length12
Median length9
Mean length7.003982023
Min length3

Characters and Unicode

Total characters14591837
Distinct characters29
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTAXA FIXA
2nd rowTAXA FIXA
3rd rowTAXA FIXA
4th rowTAXA FIXA
5th rowTAXA FIXA
ValueCountFrequency (%)
TAXA FIXA1215892
58.4%
TJLP563382
27.0%
TJ462159600
 
7.7%
TLP79331
 
3.8%
SELIC56629
 
2.7%
US$ / CESTA5280
 
0.3%
TJ4532973
 
0.1%
75% da SELIC230
 
< 0.1%
90% da SELIC28
 
< 0.1%
OUTROS16
 
< 0.1%
2021-08-18T23:28:07.785845image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
fixa1215892
36.7%
taxa1215892
36.7%
tjlp563382
17.0%
tj462159600
 
4.8%
tlp79331
 
2.4%
selic56887
 
1.7%
cesta5280
 
0.2%
us5280
 
0.2%
5280
 
0.2%
tj4532973
 
0.1%
Other values (5)534
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
A3652958
25.0%
X2431784
16.7%
T2026474
13.9%
I1272779
 
8.7%
1226968
 
8.4%
F1215894
 
8.3%
J725955
 
5.0%
L699600
 
4.8%
P642713
 
4.4%
4162573
 
1.1%
Other values (19)534139
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter12865300
88.2%
Space Separator1226968
 
8.4%
Decimal Number488235
 
3.3%
Other Punctuation5538
 
< 0.1%
Currency Symbol5280
 
< 0.1%
Lowercase Letter516
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
A3652958
28.4%
X2431784
18.9%
T2026474
15.8%
I1272779
 
9.9%
F1215894
 
9.5%
J725955
 
5.6%
L699600
 
5.4%
P642713
 
5.0%
S67463
 
0.5%
C62167
 
0.5%
Other values (5)67513
 
0.5%
ValueCountFrequency (%)
4162573
33.3%
6159600
32.7%
2159600
32.7%
53203
 
0.7%
32973
 
0.6%
7230
 
< 0.1%
928
 
< 0.1%
028
 
< 0.1%
ValueCountFrequency (%)
/5280
95.3%
%258
 
4.7%
ValueCountFrequency (%)
d258
50.0%
a258
50.0%
ValueCountFrequency (%)
1226968
100.0%
ValueCountFrequency (%)
$5280
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin12865816
88.2%
Common1726021
 
11.8%

Most frequent character per script

ValueCountFrequency (%)
A3652958
28.4%
X2431784
18.9%
T2026474
15.8%
I1272779
 
9.9%
F1215894
 
9.5%
J725955
 
5.6%
L699600
 
5.4%
P642713
 
5.0%
S67463
 
0.5%
C62167
 
0.5%
Other values (7)68029
 
0.5%
ValueCountFrequency (%)
1226968
71.1%
4162573
 
9.4%
6159600
 
9.2%
2159600
 
9.2%
$5280
 
0.3%
/5280
 
0.3%
53203
 
0.2%
32973
 
0.2%
%258
 
< 0.1%
7230
 
< 0.1%
Other values (2)56
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII14591837
100.0%

Most frequent character per block

ValueCountFrequency (%)
A3652958
25.0%
X2431784
16.7%
T2026474
13.9%
I1272779
 
8.7%
1226968
 
8.4%
F1215894
 
8.3%
J725955
 
5.0%
L699600
 
4.8%
P642713
 
4.4%
4162573
 
1.1%
Other values (19)534139
 
3.7%

juros
Real number (ℝ≥0)

Distinct1973
Distinct (%)0.1%
Missing436
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean5.628104086
Minimum0.33
Maximum53
Zeros0
Zeros (%)0.0%
Memory size15.9 MiB
2021-08-18T23:28:08.127159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.33
5-th percentile2.4
Q13.9
median5.1
Q37
95-th percentile10
Maximum53
Range52.67
Interquartile range (IQR)3.1

Descriptive statistics

Standard deviation2.781144032
Coefficient of variation (CV)0.4941529135
Kurtosis5.16200662
Mean5.628104086
Median Absolute Deviation (MAD)1.6
Skewness1.674332276
Sum11722929.96
Variance7.734762125
MonotocityNot monotonic
2021-08-18T23:28:08.438711image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4174756
 
8.4%
6153060
 
7.3%
3134376
 
6.4%
8.75123765
 
5.9%
5.5115703
 
5.6%
4.5115418
 
5.5%
7110181
 
5.3%
2.593453
 
4.5%
870755
 
3.4%
3.960636
 
2.9%
Other values (1963)930824
44.7%
ValueCountFrequency (%)
0.331
 
< 0.1%
0.596
 
< 0.1%
0.733
 
< 0.1%
0.752
 
< 0.1%
0.8114
< 0.1%
ValueCountFrequency (%)
531
< 0.1%
28.211
< 0.1%
27.511
< 0.1%
27.11
< 0.1%
27.051
< 0.1%

prazo_carencia_meses
Real number (ℝ≥0)

ZEROS

Distinct57
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.296293541
Minimum0
Maximum120
Zeros309940
Zeros (%)14.9%
Memory size15.9 MiB
2021-08-18T23:28:08.749750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median3
Q36
95-th percentile24
Maximum120
Range120
Interquartile range (IQR)3

Descriptive statistics

Standard deviation6.92397936
Coefficient of variation (CV)1.099691321
Kurtosis13.82370159
Mean6.296293541
Median Absolute Deviation (MAD)3
Skewness2.849542919
Sum13117465
Variance47.94149017
MonotocityNot monotonic
2021-08-18T23:28:09.112866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3749616
36.0%
6589245
28.3%
0309940
14.9%
12271805
 
13.0%
24106714
 
5.1%
3628094
 
1.3%
187303
 
0.4%
96590
 
0.3%
51905
 
0.1%
481809
 
0.1%
Other values (47)10342
 
0.5%
ValueCountFrequency (%)
0309940
14.9%
11135
 
0.1%
21049
 
0.1%
3749616
36.0%
4826
 
< 0.1%
ValueCountFrequency (%)
1201
 
< 0.1%
1081
 
< 0.1%
96230
< 0.1%
952
 
< 0.1%
9023
 
< 0.1%

prazo_amortizacao_meses
Real number (ℝ≥0)

Distinct162
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.87461091
Minimum0
Maximum360
Zeros764
Zeros (%)< 0.1%
Memory size15.9 MiB
2021-08-18T23:28:09.469975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile24
Q145
median54
Q357
95-th percentile96
Maximum360
Range360
Interquartile range (IQR)12

Descriptive statistics

Standard deviation18.66029
Coefficient of variation (CV)0.3463651929
Kurtosis2.607520269
Mean53.87461091
Median Absolute Deviation (MAD)6
Skewness0.9448430367
Sum112240371
Variance348.2064228
MonotocityNot monotonic
2021-08-18T23:28:09.799260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57468410
22.5%
54327863
15.7%
48213696
10.3%
60204193
9.8%
45116621
 
5.6%
36113295
 
5.4%
3382099
 
3.9%
9669933
 
3.4%
4262683
 
3.0%
2457053
 
2.7%
Other values (152)367517
17.6%
ValueCountFrequency (%)
0764
< 0.1%
1560
< 0.1%
2113
 
< 0.1%
3831
< 0.1%
4379
< 0.1%
ValueCountFrequency (%)
3601
 
< 0.1%
2343
 
< 0.1%
2313
 
< 0.1%
2302
 
< 0.1%
2288
< 0.1%

modalidade_de_apoio
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
REEMBOLSÁVEL
2083363 

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters25000356
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowREEMBOLSÁVEL
2nd rowREEMBOLSÁVEL
3rd rowREEMBOLSÁVEL
4th rowREEMBOLSÁVEL
5th rowREEMBOLSÁVEL
ValueCountFrequency (%)
REEMBOLSÁVEL2083363
100.0%
2021-08-18T23:28:10.376721image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-08-18T23:28:10.580085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
reembolsável2083363
100.0%

Most occurring characters

ValueCountFrequency (%)
E6250089
25.0%
L4166726
16.7%
R2083363
 
8.3%
M2083363
 
8.3%
B2083363
 
8.3%
O2083363
 
8.3%
S2083363
 
8.3%
Á2083363
 
8.3%
V2083363
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter25000356
100.0%

Most frequent character per category

ValueCountFrequency (%)
E6250089
25.0%
L4166726
16.7%
R2083363
 
8.3%
M2083363
 
8.3%
B2083363
 
8.3%
O2083363
 
8.3%
S2083363
 
8.3%
Á2083363
 
8.3%
V2083363
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Latin25000356
100.0%

Most frequent character per script

ValueCountFrequency (%)
E6250089
25.0%
L4166726
16.7%
R2083363
 
8.3%
M2083363
 
8.3%
B2083363
 
8.3%
O2083363
 
8.3%
S2083363
 
8.3%
Á2083363
 
8.3%
V2083363
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII22916993
91.7%
None2083363
 
8.3%

Most frequent character per block

ValueCountFrequency (%)
E6250089
27.3%
L4166726
18.2%
R2083363
 
9.1%
M2083363
 
9.1%
B2083363
 
9.1%
O2083363
 
9.1%
S2083363
 
9.1%
V2083363
 
9.1%
ValueCountFrequency (%)
Á2083363
100.0%

forma_de_apoio
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
INDIRETA
2083363 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters16666904
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowINDIRETA
2nd rowINDIRETA
3rd rowINDIRETA
4th rowINDIRETA
5th rowINDIRETA
ValueCountFrequency (%)
INDIRETA2083363
100.0%
2021-08-18T23:28:11.065467image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-08-18T23:28:11.246693image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
indireta2083363
100.0%

Most occurring characters

ValueCountFrequency (%)
I4166726
25.0%
N2083363
12.5%
D2083363
12.5%
R2083363
12.5%
E2083363
12.5%
T2083363
12.5%
A2083363
12.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter16666904
100.0%

Most frequent character per category

ValueCountFrequency (%)
I4166726
25.0%
N2083363
12.5%
D2083363
12.5%
R2083363
12.5%
E2083363
12.5%
T2083363
12.5%
A2083363
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin16666904
100.0%

Most frequent character per script

ValueCountFrequency (%)
I4166726
25.0%
N2083363
12.5%
D2083363
12.5%
R2083363
12.5%
E2083363
12.5%
T2083363
12.5%
A2083363
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII16666904
100.0%

Most frequent character per block

ValueCountFrequency (%)
I4166726
25.0%
N2083363
12.5%
D2083363
12.5%
R2083363
12.5%
E2083363
12.5%
T2083363
12.5%
A2083363
12.5%

produto
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
BNDES FINAME
1527673 
BNDES AUTOMÁTICO
516213 
BNDES FINAME LEASING
 
24799
BNDES FINAME AGRÍCOLA
 
14678

Length

Max length21
Median length12
Mean length13.14974971
Min length12

Characters and Unicode

Total characters27395702
Distinct characters19
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBNDES AUTOMÁTICO
2nd rowBNDES AUTOMÁTICO
3rd rowBNDES AUTOMÁTICO
4th rowBNDES AUTOMÁTICO
5th rowBNDES AUTOMÁTICO
ValueCountFrequency (%)
BNDES FINAME1527673
73.3%
BNDES AUTOMÁTICO516213
 
24.8%
BNDES FINAME LEASING24799
 
1.2%
BNDES FINAME AGRÍCOLA14678
 
0.7%
2021-08-18T23:28:11.785257image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-08-18T23:28:11.987682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
bndes2083363
49.5%
finame1567150
37.3%
automático516213
 
12.3%
leasing24799
 
0.6%
agrícola14678
 
0.3%

Most occurring characters

ValueCountFrequency (%)
N3675312
13.4%
E3675312
13.4%
A2137518
7.8%
2122840
7.7%
S2108162
7.7%
I2108162
7.7%
B2083363
7.6%
D2083363
7.6%
M2083363
7.6%
F1567150
5.7%
Other values (9)3751157
13.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter25272862
92.3%
Space Separator2122840
 
7.7%

Most frequent character per category

ValueCountFrequency (%)
N3675312
14.5%
E3675312
14.5%
A2137518
8.5%
S2108162
8.3%
I2108162
8.3%
B2083363
8.2%
D2083363
8.2%
M2083363
8.2%
F1567150
6.2%
O1047104
 
4.1%
Other values (8)2704053
10.7%
ValueCountFrequency (%)
2122840
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin25272862
92.3%
Common2122840
 
7.7%

Most frequent character per script

ValueCountFrequency (%)
N3675312
14.5%
E3675312
14.5%
A2137518
8.5%
S2108162
8.3%
I2108162
8.3%
B2083363
8.2%
D2083363
8.2%
M2083363
8.2%
F1567150
6.2%
O1047104
 
4.1%
Other values (8)2704053
10.7%
ValueCountFrequency (%)
2122840
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII26864811
98.1%
None530891
 
1.9%

Most frequent character per block

ValueCountFrequency (%)
N3675312
13.7%
E3675312
13.7%
A2137518
8.0%
2122840
7.9%
S2108162
7.8%
I2108162
7.8%
B2083363
7.8%
D2083363
7.8%
M2083363
7.8%
F1567150
5.8%
Other values (7)3220266
12.0%
ValueCountFrequency (%)
Á516213
97.2%
Í14678
 
2.8%

instrumento_financeiro
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct80
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
BK AQUISIÇÃO E COMERCIALIZAÇÃO
589349 
PSI - BK - Ônibus e Caminhão
530980 
PSI - BK - Demais Itens
225933 
OUTROS
184381 
PRONAF INVESTIMENTO
160735 
Other values (75)
391985 

Length

Max length65
Median length28
Mean length23.48336896
Min length5

Characters and Unicode

Total characters48924382
Distinct characters60
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowOUTROS
2nd rowPRONAF INVESTIMENTO
3rd rowPRONAF INVESTIMENTO
4th rowPRONAF INVESTIMENTO
5th rowPRONAF INVESTIMENTO
ValueCountFrequency (%)
BK AQUISIÇÃO E COMERCIALIZAÇÃO589349
28.3%
PSI - BK - Ônibus e Caminhão530980
25.5%
PSI - BK - Demais Itens225933
 
10.8%
OUTROS184381
 
8.9%
PRONAF INVESTIMENTO160735
 
7.7%
BNDES GIRO80381
 
3.9%
MODERAGRO68409
 
3.3%
MODERINFRA50139
 
2.4%
LINHA EMPRÉSTIMO PARA MICRO E PEQUENAS EMPRESAS43278
 
2.1%
BNDES PROCAMINHONEIRO - Equalizado33661
 
1.6%
Other values (70)116117
 
5.6%
2021-08-18T23:28:12.809926image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1578436
17.6%
bk1352201
15.1%
e1174671
13.1%
psi762909
8.5%
aquisição590070
 
6.6%
comercialização589349
 
6.6%
caminhão530980
 
5.9%
ônibus530980
 
5.9%
demais226028
 
2.5%
itens225933
 
2.5%
Other values (107)1384039
15.5%

Most occurring characters

ValueCountFrequency (%)
6862233
 
14.0%
I4055456
 
8.3%
O3036849
 
6.2%
A2427318
 
5.0%
E2249286
 
4.6%
S2070122
 
4.2%
C1881624
 
3.8%
R1698579
 
3.5%
-1581694
 
3.2%
B1525013
 
3.1%
Other values (50)21536208
44.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter31033279
63.4%
Lowercase Letter9433760
 
19.3%
Space Separator6862233
 
14.0%
Dash Punctuation1581846
 
3.2%
Other Punctuation13264
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
I4055456
13.1%
O3036849
 
9.8%
A2427318
 
7.8%
E2249286
 
7.2%
S2070122
 
6.7%
C1881624
 
6.1%
R1698579
 
5.5%
B1525013
 
4.9%
K1352201
 
4.4%
P1255301
 
4.0%
Other values (20)9481530
30.6%
ValueCountFrequency (%)
i1340650
14.2%
n1288556
13.7%
e983221
10.4%
s982949
10.4%
a867773
9.2%
m756913
8.0%
u588790
6.2%
o584111
6.2%
ã531144
 
5.6%
b530980
 
5.6%
Other values (14)978673
10.4%
ValueCountFrequency (%)
,12532
94.5%
:721
 
5.4%
&11
 
0.1%
ValueCountFrequency (%)
-1581694
> 99.9%
152
 
< 0.1%
ValueCountFrequency (%)
6862233
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin40467039
82.7%
Common8457343
 
17.3%

Most frequent character per script

ValueCountFrequency (%)
I4055456
 
10.0%
O3036849
 
7.5%
A2427318
 
6.0%
E2249286
 
5.6%
S2070122
 
5.1%
C1881624
 
4.6%
R1698579
 
4.2%
B1525013
 
3.8%
K1352201
 
3.3%
i1340650
 
3.3%
Other values (44)18829941
46.5%
ValueCountFrequency (%)
6862233
81.1%
-1581694
 
18.7%
,12532
 
0.1%
:721
 
< 0.1%
152
 
< 0.1%
&11
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII45436377
92.9%
None3487853
 
7.1%
Punctuation152
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
6862233
 
15.1%
I4055456
 
8.9%
O3036849
 
6.7%
A2427318
 
5.3%
E2249286
 
5.0%
S2070122
 
4.6%
C1881624
 
4.1%
R1698579
 
3.7%
-1581694
 
3.5%
B1525013
 
3.4%
Other values (38)18048203
39.7%
ValueCountFrequency (%)
Ç1184500
34.0%
Ã1180751
33.9%
ã531144
15.2%
Ô530980
15.2%
É52567
 
1.5%
Ú5224
 
0.1%
Á2401
 
0.1%
ç164
 
< 0.1%
Ó49
 
< 0.1%
Ê48
 
< 0.1%
ValueCountFrequency (%)
152
100.0%

inovacao
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
NÃO
2082863 
SIM
 
500

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6250089
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNÃO
2nd rowNÃO
3rd rowNÃO
4th rowNÃO
5th rowNÃO
ValueCountFrequency (%)
NÃO2082863
> 99.9%
SIM500
 
< 0.1%
2021-08-18T23:28:13.344241image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-08-18T23:28:13.587316image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
não2082863
> 99.9%
sim500
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
N2082863
33.3%
Ã2082863
33.3%
O2082863
33.3%
S500
 
< 0.1%
I500
 
< 0.1%
M500
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter6250089
100.0%

Most frequent character per category

ValueCountFrequency (%)
N2082863
33.3%
Ã2082863
33.3%
O2082863
33.3%
S500
 
< 0.1%
I500
 
< 0.1%
M500
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin6250089
100.0%

Most frequent character per script

ValueCountFrequency (%)
N2082863
33.3%
Ã2082863
33.3%
O2082863
33.3%
S500
 
< 0.1%
I500
 
< 0.1%
M500
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII4167226
66.7%
None2082863
33.3%

Most frequent character per block

ValueCountFrequency (%)
N2082863
50.0%
O2082863
50.0%
S500
 
< 0.1%
I500
 
< 0.1%
M500
 
< 0.1%
ValueCountFrequency (%)
Ã2082863
100.0%

area_operacional
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
AREA DE OPERACOES E CANAIS DIGITAIS
2082933 
AREA DE MERC CAP, PARTIC E REEST DE EMPRESAS
 
429
AREA DE INDUSTRIA E SERVICOS
 
1

Length

Max length44
Median length35
Mean length35.00184989
Min length28

Characters and Unicode

Total characters72921559
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowAREA DE OPERACOES E CANAIS DIGITAIS
2nd rowAREA DE OPERACOES E CANAIS DIGITAIS
3rd rowAREA DE OPERACOES E CANAIS DIGITAIS
4th rowAREA DE OPERACOES E CANAIS DIGITAIS
5th rowAREA DE OPERACOES E CANAIS DIGITAIS
ValueCountFrequency (%)
AREA DE OPERACOES E CANAIS DIGITAIS2082933
> 99.9%
AREA DE MERC CAP, PARTIC E REEST DE EMPRESAS429
 
< 0.1%
AREA DE INDUSTRIA E SERVICOS1
 
< 0.1%
2021-08-18T23:28:14.140134image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-08-18T23:28:14.363558image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
de2083792
16.7%
area2083363
16.7%
e2083363
16.7%
digitais2082933
16.7%
operacoes2082933
16.7%
canais2082933
16.7%
reest429
 
< 0.1%
cap429
 
< 0.1%
empresas429
 
< 0.1%
partic429
 
< 0.1%
Other values (3)431
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
A12499746
17.1%
E10418530
14.3%
10418101
14.3%
I8332164
11.4%
S6250089
8.6%
R4168014
 
5.7%
C4167154
 
5.7%
D4166726
 
5.7%
O4165867
 
5.7%
P2084220
 
2.9%
Other values (7)6250948
8.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter62503029
85.7%
Space Separator10418101
 
14.3%
Other Punctuation429
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
A12499746
20.0%
E10418530
16.7%
I8332164
13.3%
S6250089
10.0%
R4168014
 
6.7%
C4167154
 
6.7%
D4166726
 
6.7%
O4165867
 
6.7%
P2084220
 
3.3%
T2083792
 
3.3%
Other values (5)4166727
 
6.7%
ValueCountFrequency (%)
10418101
100.0%
ValueCountFrequency (%)
,429
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin62503029
85.7%
Common10418530
 
14.3%

Most frequent character per script

ValueCountFrequency (%)
A12499746
20.0%
E10418530
16.7%
I8332164
13.3%
S6250089
10.0%
R4168014
 
6.7%
C4167154
 
6.7%
D4166726
 
6.7%
O4165867
 
6.7%
P2084220
 
3.3%
T2083792
 
3.3%
Other values (5)4166727
 
6.7%
ValueCountFrequency (%)
10418101
> 99.9%
,429
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII72921559
100.0%

Most frequent character per block

ValueCountFrequency (%)
A12499746
17.1%
E10418530
14.3%
10418101
14.3%
I8332164
11.4%
S6250089
8.6%
R4168014
 
5.7%
C4167154
 
5.7%
D4166726
 
5.7%
O4165867
 
5.7%
P2084220
 
2.9%
Other values (7)6250948
8.6%

setor_cnae
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
COMERCIO E SERVICOS
1426476 
AGROPECUÁRIA E PESCA
334612 
INDUSTRIA DE TRANSFORMAÇÃO
307353 
INDUSTRIA EXTRATIVA
 
14922

Length

Max length26
Median length19
Mean length20.19330285
Min length19

Characters and Unicode

Total characters42069980
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAGROPECUÁRIA E PESCA
2nd rowAGROPECUÁRIA E PESCA
3rd rowAGROPECUÁRIA E PESCA
4th rowAGROPECUÁRIA E PESCA
5th rowAGROPECUÁRIA E PESCA
ValueCountFrequency (%)
COMERCIO E SERVICOS1426476
68.5%
AGROPECUÁRIA E PESCA334612
 
16.1%
INDUSTRIA DE TRANSFORMAÇÃO307353
 
14.8%
INDUSTRIA EXTRATIVA14922
 
0.7%
2021-08-18T23:28:15.178286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-08-18T23:28:15.376226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
e1761088
28.2%
comercio1426476
22.9%
servicos1426476
22.9%
pesca334612
 
5.4%
agropecuária334612
 
5.4%
industria322275
 
5.2%
transformação307353
 
4.9%
de307353
 
4.9%
extrativa14922
 
0.2%

Most occurring characters

ValueCountFrequency (%)
E5605539
13.3%
O5228746
12.4%
C4948652
11.8%
R4474079
10.6%
4151804
9.9%
I3847036
9.1%
S3817192
9.1%
A1970661
 
4.7%
M1733829
 
4.1%
V1441398
 
3.4%
Other values (11)4851044
11.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter37918176
90.1%
Space Separator4151804
 
9.9%

Most frequent character per category

ValueCountFrequency (%)
E5605539
14.8%
O5228746
13.8%
C4948652
13.1%
R4474079
11.8%
I3847036
10.1%
S3817192
10.1%
A1970661
 
5.2%
M1733829
 
4.6%
V1441398
 
3.8%
P669224
 
1.8%
Other values (10)4181820
11.0%
ValueCountFrequency (%)
4151804
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin37918176
90.1%
Common4151804
 
9.9%

Most frequent character per script

ValueCountFrequency (%)
E5605539
14.8%
O5228746
13.8%
C4948652
13.1%
R4474079
11.8%
I3847036
10.1%
S3817192
10.1%
A1970661
 
5.2%
M1733829
 
4.6%
V1441398
 
3.8%
P669224
 
1.8%
Other values (10)4181820
11.0%
ValueCountFrequency (%)
4151804
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII41120662
97.7%
None949318
 
2.3%

Most frequent character per block

ValueCountFrequency (%)
E5605539
13.6%
O5228746
12.7%
C4948652
12.0%
R4474079
10.9%
4151804
10.1%
I3847036
9.4%
S3817192
9.3%
A1970661
 
4.8%
M1733829
 
4.2%
V1441398
 
3.5%
Other values (8)3901726
9.5%
ValueCountFrequency (%)
Á334612
35.2%
Ç307353
32.4%
Ã307353
32.4%

subsetor_cnae_agrupado
Categorical

HIGH CORRELATION

Distinct44
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
Transporte terrestre
805177 
Agropecuária
334612 
Comércio
322068 
Construção
109010 
Produtos Alimentícios
 
77527
Other values (39)
434969 

Length

Max length31
Median length20
Mean length16.66774585
Min length4

Characters and Unicode

Total characters34724965
Distinct characters49
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAgropecuária
2nd rowAgropecuária
3rd rowAgropecuária
4th rowAgropecuária
5th rowAgropecuária
ValueCountFrequency (%)
Transporte terrestre805177
38.6%
Agropecuária334612
16.1%
Comércio322068
 
15.5%
Construção109010
 
5.2%
Produtos Alimentícios77527
 
3.7%
Ativ imobil, profissional e adm77399
 
3.7%
Ativ aux transporte e entrega43273
 
2.1%
Mineral não metálico26936
 
1.3%
Borracha e plástico24464
 
1.2%
Produto de metal23699
 
1.1%
Other values (34)239198
 
11.5%
2021-08-18T23:28:16.002783image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
transporte850234
21.4%
terrestre805177
20.3%
agropecuária334612
 
8.4%
comércio322068
 
8.1%
e263162
 
6.6%
ativ135278
 
3.4%
construção109010
 
2.7%
produtos82292
 
2.1%
alimentícios77527
 
2.0%
imobil77399
 
2.0%
Other values (77)911009
23.0%

Most occurring characters

ValueCountFrequency (%)
r5742453
16.5%
e4492028
12.9%
t3250914
9.4%
o2989078
 
8.6%
s2322891
 
6.7%
a1899639
 
5.5%
1884405
 
5.4%
i1612225
 
4.6%
n1349938
 
3.9%
p1346217
 
3.9%
Other values (39)7835177
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter30509716
87.9%
Uppercase Letter2176356
 
6.3%
Space Separator1884405
 
5.4%
Other Punctuation154488
 
0.4%

Most frequent character per category

ValueCountFrequency (%)
r5742453
18.8%
e4492028
14.7%
t3250914
10.7%
o2989078
9.8%
s2322891
7.6%
a1899639
 
6.2%
i1612225
 
5.3%
n1349938
 
4.4%
p1346217
 
4.4%
c956990
 
3.1%
Other values (21)4547343
14.9%
ValueCountFrequency (%)
T816965
37.5%
A558303
25.7%
C465742
21.4%
P106535
 
4.9%
M94180
 
4.3%
B33400
 
1.5%
E26320
 
1.2%
I19446
 
0.9%
Á14100
 
0.6%
Q13820
 
0.6%
Other values (5)27545
 
1.3%
ValueCountFrequency (%)
,150960
97.7%
.3528
 
2.3%
ValueCountFrequency (%)
1884405
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin32686072
94.1%
Common2038893
 
5.9%

Most frequent character per script

ValueCountFrequency (%)
r5742453
17.6%
e4492028
13.7%
t3250914
9.9%
o2989078
9.1%
s2322891
 
7.1%
a1899639
 
5.8%
i1612225
 
4.9%
n1349938
 
4.1%
p1346217
 
4.1%
c956990
 
2.9%
Other values (36)6723699
20.6%
ValueCountFrequency (%)
1884405
92.4%
,150960
 
7.4%
.3528
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII33441982
96.3%
None1282983
 
3.7%

Most frequent character per block

ValueCountFrequency (%)
r5742453
17.2%
e4492028
13.4%
t3250914
9.7%
o2989078
8.9%
s2322891
 
6.9%
a1899639
 
5.7%
1884405
 
5.6%
i1612225
 
4.8%
n1349938
 
4.0%
p1346217
 
4.0%
Other values (29)6552194
19.6%
ValueCountFrequency (%)
á431668
33.6%
é322390
25.1%
ã170946
 
13.3%
ç157632
 
12.3%
í111881
 
8.7%
ó37862
 
3.0%
ú23463
 
1.8%
Á14100
 
1.1%
ê9933
 
0.8%
õ3108
 
0.2%

subsetor_cnae_codigo
Categorical

HIGH CARDINALITY

Distinct1640
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
H4930202
614726 
A0100000
142064 
H4930201
 
35378
H4930203
 
32979
F4313400
 
32540
Other values (1635)
1225676 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters16666904
Distinct characters29
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)< 0.1%

Sample

1st rowA0119900
2nd rowA0100000
3rd rowA0100000
4th rowA0100000
5th rowA0100000
ValueCountFrequency (%)
H4930202614726
29.5%
A0100000142064
 
6.8%
H493020135378
 
1.7%
H493020332979
 
1.6%
F431340032540
 
1.6%
A011560027244
 
1.3%
H521179926447
 
1.3%
G474409924336
 
1.2%
H493020024213
 
1.2%
H492130123875
 
1.1%
Other values (1630)1099561
52.8%
2021-08-18T23:28:16.791416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
h4930202614726
29.5%
a0100000142064
 
6.8%
h493020135378
 
1.7%
h493020332979
 
1.6%
f431340032540
 
1.6%
a011560027244
 
1.3%
h521179926447
 
1.3%
g474409924336
 
1.2%
h493020024213
 
1.2%
h492130123875
 
1.1%
Other values (1630)1099561
52.8%

Most occurring characters

ValueCountFrequency (%)
04609952
27.7%
22311829
13.9%
11693045
 
10.2%
41646562
 
9.9%
91504208
 
9.0%
31377520
 
8.3%
H849303
 
5.1%
7496894
 
3.0%
5399784
 
2.4%
A334612
 
2.0%
Other values (19)1443195
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number14583541
87.5%
Uppercase Letter2083363
 
12.5%

Most frequent character per category

ValueCountFrequency (%)
H849303
40.8%
A334612
 
16.1%
G322068
 
15.5%
C307353
 
14.8%
F109010
 
5.2%
N66673
 
3.2%
B14922
 
0.7%
E14100
 
0.7%
I12268
 
0.6%
K10452
 
0.5%
Other values (9)42602
 
2.0%
ValueCountFrequency (%)
04609952
31.6%
22311829
15.9%
11693045
 
11.6%
41646562
 
11.3%
91504208
 
10.3%
31377520
 
9.4%
7496894
 
3.4%
5399784
 
2.7%
6333380
 
2.3%
8210367
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common14583541
87.5%
Latin2083363
 
12.5%

Most frequent character per script

ValueCountFrequency (%)
H849303
40.8%
A334612
 
16.1%
G322068
 
15.5%
C307353
 
14.8%
F109010
 
5.2%
N66673
 
3.2%
B14922
 
0.7%
E14100
 
0.7%
I12268
 
0.6%
K10452
 
0.5%
Other values (9)42602
 
2.0%
ValueCountFrequency (%)
04609952
31.6%
22311829
15.9%
11693045
 
11.6%
41646562
 
11.3%
91504208
 
10.3%
31377520
 
9.4%
7496894
 
3.4%
5399784
 
2.7%
6333380
 
2.3%
8210367
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII16666904
100.0%

Most frequent character per block

ValueCountFrequency (%)
04609952
27.7%
22311829
13.9%
11693045
 
10.2%
41646562
 
9.9%
91504208
 
9.0%
31377520
 
8.3%
H849303
 
5.1%
7496894
 
3.0%
5399784
 
2.4%
A334612
 
2.0%
Other values (19)1443195
 
8.7%

subsetor_cnae_nome
Categorical

HIGH CARDINALITY

Distinct1604
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
TRANSP ROD CARGA EXC PROD PERIG MUDANCA INTER-MUN-EST-NACIONAL
614726 
AGRICULTURA, PECUARIA E SERVICOS RELACIONADOS
142064 
TRANSP ROD CARGA EXCETO PRODUTOS PERIGOSOS E MUDANCAS, MUNICIPAL
 
35378
TRANSPORTE RODOVIARIO DE PRODUTOS PERIGOSOS
 
32979
OBRAS DE TERRAPLENAGEM
 
32540
Other values (1599)
1225676 

Length

Max length65
Median length60
Mean length50.5719157
Min length5

Characters and Unicode

Total characters105359658
Distinct characters34
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)< 0.1%

Sample

1st rowCULT PLANTAS LAVOURA TEMPORARIA NAO ESPECIFICADAS ANTERIORMENTE
2nd rowAGRICULTURA, PECUARIA E SERVICOS RELACIONADOS
3rd rowAGRICULTURA, PECUARIA E SERVICOS RELACIONADOS
4th rowAGRICULTURA, PECUARIA E SERVICOS RELACIONADOS
5th rowAGRICULTURA, PECUARIA E SERVICOS RELACIONADOS
ValueCountFrequency (%)
TRANSP ROD CARGA EXC PROD PERIG MUDANCA INTER-MUN-EST-NACIONAL614726
29.5%
AGRICULTURA, PECUARIA E SERVICOS RELACIONADOS142064
 
6.8%
TRANSP ROD CARGA EXCETO PRODUTOS PERIGOSOS E MUDANCAS, MUNICIPAL35378
 
1.7%
TRANSPORTE RODOVIARIO DE PRODUTOS PERIGOSOS32979
 
1.6%
OBRAS DE TERRAPLENAGEM32540
 
1.6%
CULTIVO DE SOJA27244
 
1.3%
DEPOSITO MERCADORIA P/TERCEIRO EXC ARMAZEM GERAL GUARDA-MOVEIS26447
 
1.3%
COMERCIO VAREJISTA DE MATERIAIS DE CONSTRUCAO EM GERAL24336
 
1.2%
TRANSPORTE RODOVIARIO DE CARGA24213
 
1.2%
TRANSP RODOV COL PASSAG C/ITINERARIO FIXO, MUNICIPAL23875
 
1.1%
Other values (1594)1099561
52.8%
2021-08-18T23:28:17.438811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de1113989
 
7.8%
transp738944
 
5.2%
carga681943
 
4.8%
rod673595
 
4.7%
exc671809
 
4.7%
prod656788
 
4.6%
inter-mun-est-nacional639738
 
4.5%
perig614726
 
4.3%
mudanca614726
 
4.3%
e512521
 
3.6%
Other values (2054)7419286
51.7%

Most occurring characters

ValueCountFrequency (%)
12256299
11.6%
A11937607
11.3%
E9201338
 
8.7%
R9146272
 
8.7%
O7856703
 
7.5%
C6731271
 
6.4%
I6426683
 
6.1%
N5893313
 
5.6%
S5287903
 
5.0%
T4980106
 
4.7%
Other values (24)25642163
24.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter90471114
85.9%
Space Separator12256299
 
11.6%
Dash Punctuation2066921
 
2.0%
Other Punctuation542969
 
0.5%
Open Punctuation11125
 
< 0.1%
Close Punctuation11125
 
< 0.1%
Lowercase Letter105
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
A11937607
13.2%
E9201338
10.2%
R9146272
10.1%
O7856703
8.7%
C6731271
 
7.4%
I6426683
 
7.1%
N5893313
 
6.5%
S5287903
 
5.8%
T4980106
 
5.5%
D4495877
 
5.0%
Other values (16)18514041
20.5%
ValueCountFrequency (%)
,338119
62.3%
/204503
37.7%
.347
 
0.1%
ValueCountFrequency (%)
12256299
100.0%
ValueCountFrequency (%)
-2066921
100.0%
ValueCountFrequency (%)
(11125
100.0%
ValueCountFrequency (%)
)11125
100.0%
ValueCountFrequency (%)
á105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin90471219
85.9%
Common14888439
 
14.1%

Most frequent character per script

ValueCountFrequency (%)
A11937607
13.2%
E9201338
10.2%
R9146272
10.1%
O7856703
8.7%
C6731271
 
7.4%
I6426683
 
7.1%
N5893313
 
6.5%
S5287903
 
5.8%
T4980106
 
5.5%
D4495877
 
5.0%
Other values (17)18514146
20.5%
ValueCountFrequency (%)
12256299
82.3%
-2066921
 
13.9%
,338119
 
2.3%
/204503
 
1.4%
(11125
 
0.1%
)11125
 
0.1%
.347
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII105358693
> 99.9%
None965
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
12256299
11.6%
A11937607
11.3%
E9201338
 
8.7%
R9146272
 
8.7%
O7856703
 
7.5%
C6731271
 
6.4%
I6426683
 
6.1%
N5893313
 
5.6%
S5287903
 
5.0%
T4980106
 
4.7%
Other values (22)25641198
24.3%
ValueCountFrequency (%)
Ç860
89.1%
á105
 
10.9%

setor_bndes
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
INFRA-ESTRUTURA
870722 
COMERCIO/SERVICOS
555754 
AGROPECUÁRIA
334612 
INDUSTRIA
322275 

Length

Max length17
Median length15
Mean length14.12354304
Min length9

Characters and Unicode

Total characters29424467
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAGROPECUÁRIA
2nd rowAGROPECUÁRIA
3rd rowAGROPECUÁRIA
4th rowAGROPECUÁRIA
5th rowAGROPECUÁRIA
ValueCountFrequency (%)
INFRA-ESTRUTURA870722
41.8%
COMERCIO/SERVICOS555754
26.7%
AGROPECUÁRIA334612
 
16.1%
INDUSTRIA322275
 
15.5%
2021-08-18T23:28:18.222617image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-08-18T23:28:18.443699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
infra-estrutura870722
41.8%
comercio/servicos555754
26.7%
agropecuária334612
 
16.1%
industria322275
 
15.5%

Most occurring characters

ValueCountFrequency (%)
R4715173
16.0%
I2961392
10.1%
A2732943
9.3%
U2398331
8.2%
E2316842
7.9%
S2304505
7.8%
T2063719
7.0%
O2001874
6.8%
C2001874
6.8%
N1192997
 
4.1%
Other values (9)4734817
16.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter27997991
95.2%
Dash Punctuation870722
 
3.0%
Other Punctuation555754
 
1.9%

Most frequent character per category

ValueCountFrequency (%)
R4715173
16.8%
I2961392
10.6%
A2732943
9.8%
U2398331
8.6%
E2316842
8.3%
S2304505
8.2%
T2063719
7.4%
O2001874
7.2%
C2001874
7.2%
N1192997
 
4.3%
Other values (7)3308341
11.8%
ValueCountFrequency (%)
-870722
100.0%
ValueCountFrequency (%)
/555754
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin27997991
95.2%
Common1426476
 
4.8%

Most frequent character per script

ValueCountFrequency (%)
R4715173
16.8%
I2961392
10.6%
A2732943
9.8%
U2398331
8.6%
E2316842
8.3%
S2304505
8.2%
T2063719
7.4%
O2001874
7.2%
C2001874
7.2%
N1192997
 
4.3%
Other values (7)3308341
11.8%
ValueCountFrequency (%)
-870722
61.0%
/555754
39.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII29089855
98.9%
None334612
 
1.1%

Most frequent character per block

ValueCountFrequency (%)
R4715173
16.2%
I2961392
10.2%
A2732943
9.4%
U2398331
8.2%
E2316842
8.0%
S2304505
7.9%
T2063719
7.1%
O2001874
6.9%
C2001874
6.9%
N1192997
 
4.1%
Other values (8)4400205
15.1%
ValueCountFrequency (%)
Á334612
100.0%

subsetor_bndes
Categorical

HIGH CORRELATION

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
TRANSPORTE RODOVIÁRIO
804461 
COMÉRCIO E SERVIÇOS
555754 
AGROPECUÁRIA
334612 
OUTRAS
96566 
ALIMENTO E BEBIDA
86463 
Other values (15)
205507 

Length

Max length23
Median length19
Mean length17.85249618
Min length6

Characters and Unicode

Total characters37193230
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAGROPECUÁRIA
2nd rowAGROPECUÁRIA
3rd rowAGROPECUÁRIA
4th rowAGROPECUÁRIA
5th rowAGROPECUÁRIA
ValueCountFrequency (%)
TRANSPORTE RODOVIÁRIO804461
38.6%
COMÉRCIO E SERVIÇOS555754
26.7%
AGROPECUÁRIA334612
16.1%
OUTRAS96566
 
4.6%
ALIMENTO E BEBIDA86463
 
4.2%
ATV. AUX. TRANSPORTES42643
 
2.0%
METALURGIA E PRODUTOS33281
 
1.6%
MECÂNICA29057
 
1.4%
QUÍMICA E PETROQUÍMICA25356
 
1.2%
TÊXTIL E VESTUÁRIO19534
 
0.9%
Other values (10)55636
 
2.7%
2021-08-18T23:28:19.033455image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
transporte815024
18.2%
rodoviário804461
18.0%
e727555
16.2%
serviços555754
12.4%
comércio555754
12.4%
agropecuária334612
7.5%
outras96566
 
2.2%
bebida86463
 
1.9%
alimento86463
 
1.9%
transportes43578
 
1.0%
Other values (23)375109
8.4%

Most occurring characters

ValueCountFrequency (%)
O5584963
15.0%
R5364485
14.4%
I3458341
9.3%
E2860568
 
7.7%
2397976
 
6.4%
S2190240
 
5.9%
T2156153
 
5.8%
A2123584
 
5.7%
C1586639
 
4.3%
V1452304
 
3.9%
Other values (21)8017977
21.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter34695612
93.3%
Space Separator2397976
 
6.4%
Other Punctuation99642
 
0.3%

Most frequent character per category

ValueCountFrequency (%)
O5584963
16.1%
R5364485
15.5%
I3458341
10.0%
E2860568
8.2%
S2190240
 
6.3%
T2156153
 
6.2%
A2123584
 
6.1%
C1586639
 
4.6%
V1452304
 
4.2%
P1280541
 
3.7%
Other values (19)6637794
19.1%
ValueCountFrequency (%)
2397976
100.0%
ValueCountFrequency (%)
.99642
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin34695612
93.3%
Common2497618
 
6.7%

Most frequent character per script

ValueCountFrequency (%)
O5584963
16.1%
R5364485
15.5%
I3458341
10.0%
E2860568
8.2%
S2190240
 
6.3%
T2156153
 
6.2%
A2123584
 
6.1%
C1586639
 
4.6%
V1452304
 
4.2%
P1280541
 
3.7%
Other values (19)6637794
19.1%
ValueCountFrequency (%)
2397976
96.0%
.99642
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII34797678
93.6%
None2395552
 
6.4%

Most frequent character per block

ValueCountFrequency (%)
O5584963
16.0%
R5364485
15.4%
I3458341
9.9%
E2860568
8.2%
2397976
6.9%
S2190240
 
6.3%
T2156153
 
6.2%
A2123584
 
6.1%
C1586639
 
4.6%
V1452304
 
4.2%
Other values (12)5622425
16.2%
ValueCountFrequency (%)
Á1159241
48.4%
Ç559836
23.4%
É558734
23.3%
Í50712
 
2.1%
Â29057
 
1.2%
Ê19534
 
0.8%
Ú14356
 
0.6%
Õ3108
 
0.1%
Ã974
 
< 0.1%

porte_do_cliente
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
MICRO
948294 
PEQUENA
428387 
GRANDE
364372 
MÉDIA
342310 

Length

Max length7
Median length5
Mean length5.586141733
Min length5

Characters and Unicode

Total characters11637961
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMICRO
2nd rowMICRO
3rd rowMICRO
4th rowMICRO
5th rowMICRO
ValueCountFrequency (%)
MICRO948294
45.5%
PEQUENA428387
20.6%
GRANDE364372
 
17.5%
MÉDIA342310
 
16.4%
2021-08-18T23:28:19.633098image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-08-18T23:28:19.826053image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
micro948294
45.5%
pequena428387
20.6%
grande364372
 
17.5%
média342310
 
16.4%

Most occurring characters

ValueCountFrequency (%)
R1312666
11.3%
M1290604
11.1%
I1290604
11.1%
E1221146
10.5%
A1135069
9.8%
C948294
8.1%
O948294
8.1%
N792759
6.8%
D706682
6.1%
P428387
 
3.7%
Other values (4)1563456
13.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter11637961
100.0%

Most frequent character per category

ValueCountFrequency (%)
R1312666
11.3%
M1290604
11.1%
I1290604
11.1%
E1221146
10.5%
A1135069
9.8%
C948294
8.1%
O948294
8.1%
N792759
6.8%
D706682
6.1%
P428387
 
3.7%
Other values (4)1563456
13.4%

Most occurring scripts

ValueCountFrequency (%)
Latin11637961
100.0%

Most frequent character per script

ValueCountFrequency (%)
R1312666
11.3%
M1290604
11.1%
I1290604
11.1%
E1221146
10.5%
A1135069
9.8%
C948294
8.1%
O948294
8.1%
N792759
6.8%
D706682
6.1%
P428387
 
3.7%
Other values (4)1563456
13.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII11295651
97.1%
None342310
 
2.9%

Most frequent character per block

ValueCountFrequency (%)
R1312666
11.6%
M1290604
11.4%
I1290604
11.4%
E1221146
10.8%
A1135069
10.0%
C948294
8.4%
O948294
8.4%
N792759
7.0%
D706682
6.3%
P428387
 
3.8%
Other values (3)1221146
10.8%
ValueCountFrequency (%)
É342310
100.0%

natureza_do_cliente
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
PRIVADA
2079716 
ADMINISTRAÇÃO PÚBLICA DIRETA - GOVERNO MUNICIPAL
 
3011
PÚBLICA INDIRETA
 
392
ADMINISTRAÇÃO PÚBLICA DIRETA - GOVERNO ESTADUAL
 
243
ADMINISTRAÇÃO PÚBLICA DIRETA - GOVERNO FEDERAL
 
1

Length

Max length48
Median length7
Mean length7.065633305
Min length7

Characters and Unicode

Total characters14720279
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowPRIVADA
2nd rowPRIVADA
3rd rowPRIVADA
4th rowPRIVADA
5th rowPRIVADA
ValueCountFrequency (%)
PRIVADA2079716
99.8%
ADMINISTRAÇÃO PÚBLICA DIRETA - GOVERNO MUNICIPAL3011
 
0.1%
PÚBLICA INDIRETA392
 
< 0.1%
ADMINISTRAÇÃO PÚBLICA DIRETA - GOVERNO ESTADUAL243
 
< 0.1%
ADMINISTRAÇÃO PÚBLICA DIRETA - GOVERNO FEDERAL1
 
< 0.1%
2021-08-18T23:28:20.251819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-08-18T23:28:20.413831image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
privada2079716
99.0%
pública3647
 
0.2%
direta3255
 
0.2%
administração3255
 
0.2%
governo3255
 
0.2%
3255
 
0.2%
municipal3011
 
0.1%
indireta392
 
< 0.1%
estadual243
 
< 0.1%
federal1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
A4176734
28.4%
I2099934
14.3%
R2089874
14.2%
D2086862
14.2%
P2086374
14.2%
V2082971
14.2%
16667
 
0.1%
N9913
 
0.1%
O9765
 
0.1%
E7147
 
< 0.1%
Other values (13)54038
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter14700357
99.9%
Space Separator16667
 
0.1%
Dash Punctuation3255
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
A4176734
28.4%
I2099934
14.3%
R2089874
14.2%
D2086862
14.2%
P2086374
14.2%
V2082971
14.2%
N9913
 
0.1%
O9765
 
0.1%
E7147
 
< 0.1%
T7145
 
< 0.1%
Other values (11)43638
 
0.3%
ValueCountFrequency (%)
16667
100.0%
ValueCountFrequency (%)
-3255
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin14700357
99.9%
Common19922
 
0.1%

Most frequent character per script

ValueCountFrequency (%)
A4176734
28.4%
I2099934
14.3%
R2089874
14.2%
D2086862
14.2%
P2086374
14.2%
V2082971
14.2%
N9913
 
0.1%
O9765
 
0.1%
E7147
 
< 0.1%
T7145
 
< 0.1%
Other values (11)43638
 
0.3%
ValueCountFrequency (%)
16667
83.7%
-3255
 
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII14710122
99.9%
None10157
 
0.1%

Most frequent character per block

ValueCountFrequency (%)
A4176734
28.4%
I2099934
14.3%
R2089874
14.2%
D2086862
14.2%
P2086374
14.2%
V2082971
14.2%
16667
 
0.1%
N9913
 
0.1%
O9765
 
0.1%
E7147
 
< 0.1%
Other values (10)43881
 
0.3%
ValueCountFrequency (%)
Ú3647
35.9%
Ç3255
32.0%
Ã3255
32.0%

instituicao_financeira_credenciada
Categorical

HIGH CARDINALITY

Distinct127
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
BANCO BRADESCO S.A.
344854 
BANCO DO BRASIL SA
306240 
ITAU UNIBANCO S.A.
283149 
BANCO VOLKSWAGEN S.A.
275842 
BANCO MERCEDES-BENZ DO BRASIL S/A
125310 
Other values (122)
747968 

Length

Max length55
Median length19
Mean length24.19055057
Min length8

Characters and Unicode

Total characters50397698
Distinct characters40
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowBANCO COOPERATIVO SICOOB S.A.
2nd rowBANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL
3rd rowBANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL
4th rowBANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL
5th rowBANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL
ValueCountFrequency (%)
BANCO BRADESCO S.A.344854
16.6%
BANCO DO BRASIL SA306240
14.7%
ITAU UNIBANCO S.A.283149
13.6%
BANCO VOLKSWAGEN S.A.275842
13.2%
BANCO MERCEDES-BENZ DO BRASIL S/A125310
 
6.0%
BANCO SANTANDER (BRASIL) S.A.78572
 
3.8%
BANCO COOPERATIVO SICREDI S.A.62097
 
3.0%
BANCO VOLVO (BRASIL) S.A60580
 
2.9%
BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL55588
 
2.7%
CAIXA ECONOMICA FEDERAL51357
 
2.5%
Other values (117)439774
21.1%
2021-08-18T23:28:21.399861image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
banco1642994
20.0%
s.a1342663
16.3%
do607943
 
7.4%
brasil591896
 
7.2%
bradesco350846
 
4.3%
sa344800
 
4.2%
unibanco283149
 
3.4%
itau283149
 
3.4%
volkswagen275842
 
3.4%
de190450
 
2.3%
Other values (206)2310752
28.1%

Most occurring characters

ValueCountFrequency (%)
A6811382
13.5%
6141121
12.2%
O4567912
 
9.1%
S3921239
 
7.8%
N3575376
 
7.1%
C3151933
 
6.3%
B3098082
 
6.1%
E2710947
 
5.4%
.2623713
 
5.2%
I2231513
 
4.4%
Other values (30)11564480
22.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter40521599
80.4%
Space Separator6141121
 
12.2%
Other Punctuation2815011
 
5.6%
Decimal Number372723
 
0.7%
Open Punctuation186091
 
0.4%
Close Punctuation186091
 
0.4%
Dash Punctuation175062
 
0.3%

Most frequent character per category

ValueCountFrequency (%)
A6811382
16.8%
O4567912
11.3%
S3921239
9.7%
N3575376
8.8%
C3151933
7.8%
B3098082
7.6%
E2710947
 
6.7%
I2231513
 
5.5%
R2166365
 
5.3%
D1818664
 
4.5%
Other values (16)6468186
16.0%
ValueCountFrequency (%)
1137982
37.0%
091420
24.5%
791420
24.5%
444858
 
12.0%
83408
 
0.9%
21931
 
0.5%
91704
 
0.5%
ValueCountFrequency (%)
.2623713
93.2%
/189187
 
6.7%
,2111
 
0.1%
ValueCountFrequency (%)
6141121
100.0%
ValueCountFrequency (%)
(186091
100.0%
ValueCountFrequency (%)
)186091
100.0%
ValueCountFrequency (%)
-175062
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin40521599
80.4%
Common9876099
 
19.6%

Most frequent character per script

ValueCountFrequency (%)
A6811382
16.8%
O4567912
11.3%
S3921239
9.7%
N3575376
8.8%
C3151933
7.8%
B3098082
7.6%
E2710947
 
6.7%
I2231513
 
5.5%
R2166365
 
5.3%
D1818664
 
4.5%
Other values (16)6468186
16.0%
ValueCountFrequency (%)
6141121
62.2%
.2623713
26.6%
/189187
 
1.9%
(186091
 
1.9%
)186091
 
1.9%
-175062
 
1.8%
1137982
 
1.4%
091420
 
0.9%
791420
 
0.9%
444858
 
0.5%
Other values (4)9154
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII50397698
100.0%

Most frequent character per block

ValueCountFrequency (%)
A6811382
13.5%
6141121
12.2%
O4567912
 
9.1%
S3921239
 
7.8%
N3575376
 
7.1%
C3151933
 
6.3%
B3098082
 
6.1%
E2710947
 
5.4%
.2623713
 
5.2%
I2231513
 
4.4%
Other values (30)11564480
22.9%

cnpj_do_agente_financeiro
Categorical

HIGH CARDINALITY

Distinct127
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
60.746.948.0001-12
344854 
00.000.000.0001-91
306240 
60.701.190.0001-04
283149 
59.109.165.0001-49
275842 
60.814.191.0001-57
125310 
Other values (122)
747968 

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters37500534
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row02.038.232.0001-64
2nd row92.816.560.0001-37
3rd row92.816.560.0001-37
4th row92.816.560.0001-37
5th row92.816.560.0001-37
ValueCountFrequency (%)
60.746.948.0001-12344854
16.6%
00.000.000.0001-91306240
14.7%
60.701.190.0001-04283149
13.6%
59.109.165.0001-49275842
13.2%
60.814.191.0001-57125310
 
6.0%
90.400.888.0001-4278572
 
3.8%
01.181.521.0001-5562097
 
3.0%
58.017.179.0001-7060580
 
2.9%
92.816.560.0001-3755588
 
2.7%
00.360.305.0001-0451357
 
2.5%
Other values (117)439774
21.1%
2021-08-18T23:28:22.054332image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
60.746.948.0001-12344854
16.6%
00.000.000.0001-91306240
14.7%
60.701.190.0001-04283149
13.6%
59.109.165.0001-49275842
13.2%
60.814.191.0001-57125310
 
6.0%
90.400.888.0001-4278572
 
3.8%
01.181.521.0001-5562097
 
3.0%
58.017.179.0001-7060580
 
2.9%
92.816.560.0001-3755588
 
2.7%
00.360.305.0001-0451357
 
2.5%
Other values (117)439774
21.1%

Most occurring characters

ValueCountFrequency (%)
012018596
32.0%
.6250089
16.7%
15169293
13.8%
92359146
 
6.3%
-2083363
 
5.6%
61943908
 
5.2%
41927806
 
5.1%
71521249
 
4.1%
51383951
 
3.7%
81269832
 
3.4%
Other values (2)1573301
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number29167082
77.8%
Other Punctuation6250089
 
16.7%
Dash Punctuation2083363
 
5.6%

Most frequent character per category

ValueCountFrequency (%)
012018596
41.2%
15169293
17.7%
92359146
 
8.1%
61943908
 
6.7%
41927806
 
6.6%
71521249
 
5.2%
51383951
 
4.7%
81269832
 
4.4%
21058976
 
3.6%
3514325
 
1.8%
ValueCountFrequency (%)
.6250089
100.0%
ValueCountFrequency (%)
-2083363
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common37500534
100.0%

Most frequent character per script

ValueCountFrequency (%)
012018596
32.0%
.6250089
16.7%
15169293
13.8%
92359146
 
6.3%
-2083363
 
5.6%
61943908
 
5.2%
41927806
 
5.1%
71521249
 
4.1%
51383951
 
3.7%
81269832
 
3.4%
Other values (2)1573301
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII37500534
100.0%

Most frequent character per block

ValueCountFrequency (%)
012018596
32.0%
.6250089
16.7%
15169293
13.8%
92359146
 
6.3%
-2083363
 
5.6%
61943908
 
5.2%
41927806
 
5.1%
71521249
 
4.1%
51383951
 
3.7%
81269832
 
3.4%
Other values (2)1573301
 
4.2%

situacao_da_operacao
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
LIQUIDADA
1829953 
ATIVA
253410 

Length

Max length9
Median length9
Mean length8.513459728
Min length5

Characters and Unicode

Total characters17736627
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLIQUIDADA
2nd rowLIQUIDADA
3rd rowLIQUIDADA
4th rowLIQUIDADA
5th rowLIQUIDADA
ValueCountFrequency (%)
LIQUIDADA1829953
87.8%
ATIVA253410
 
12.2%
2021-08-18T23:28:22.603909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-08-18T23:28:22.779131image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
liquidada1829953
87.8%
ativa253410
 
12.2%

Most occurring characters

ValueCountFrequency (%)
A4166726
23.5%
I3913316
22.1%
D3659906
20.6%
L1829953
10.3%
Q1829953
10.3%
U1829953
10.3%
T253410
 
1.4%
V253410
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter17736627
100.0%

Most frequent character per category

ValueCountFrequency (%)
A4166726
23.5%
I3913316
22.1%
D3659906
20.6%
L1829953
10.3%
Q1829953
10.3%
U1829953
10.3%
T253410
 
1.4%
V253410
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Latin17736627
100.0%

Most frequent character per script

ValueCountFrequency (%)
A4166726
23.5%
I3913316
22.1%
D3659906
20.6%
L1829953
10.3%
Q1829953
10.3%
U1829953
10.3%
T253410
 
1.4%
V253410
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII17736627
100.0%

Most frequent character per block

ValueCountFrequency (%)
A4166726
23.5%
I3913316
22.1%
D3659906
20.6%
L1829953
10.3%
Q1829953
10.3%
U1829953
10.3%
T253410
 
1.4%
V253410
 
1.4%

Interactions

2021-08-18T23:21:38.425854image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:40.380153image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:41.583290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:43.375231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:44.795035image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:45.970020image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:47.189049image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:48.486800image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:50.033346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:51.677468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:53.042251image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:54.197673image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:55.722232image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:57.060565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:21:58.383346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:00.268702image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:01.671763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:02.910299image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:04.492670image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:06.089547image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:08.099937image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:09.669142image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:11.311826image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:12.523213image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:13.953098image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:15.389388image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:16.728752image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:18.067926image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:19.419574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-08-18T23:22:20.689339image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2021-08-18T23:28:22.949295image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-08-18T23:28:23.390139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-08-18T23:28:23.697703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-08-18T23:28:24.046335image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-08-18T23:28:24.707919image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-08-18T23:22:42.971336image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
A simple visualization of nullity by column.
2021-08-18T23:23:42.217863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-08-18T23:27:34.423913image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-08-18T23:27:41.826323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

clientecpf_cnpjufmunicipiomunicipio_codigodata_da_contratacaovalor_da_operacao_em_reaisvalor_desembolsado_reaisfonte_de_recurso_desembolsoscusto_financeirojurosprazo_carencia_mesesprazo_amortizacao_mesesmodalidade_de_apoioforma_de_apoioprodutoinstrumento_financeiroinovacaoarea_operacionalsetor_cnaesubsetor_cnae_agrupadosubsetor_cnae_codigosubsetor_cnae_nomesetor_bndessubsetor_bndesporte_do_clientenatureza_do_clienteinstituicao_financeira_credenciadacnpj_do_agente_financeirosituacao_da_operacao
0BANCO COOPERATIVO SICOOB S.A.**.*38.232/0001-**SPPEDREGULHO35370082002-01-021600016000.0RECURSOS LIVRES - TESOUROTAXA FIXA8.752436REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOOUTROSNÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0119900CULT PLANTAS LAVOURA TEMPORARIA NAO ESPECIFICADAS ANTERIORMENTEAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO COOPERATIVO SICOOB S.A.02.038.232.0001-64LIQUIDADA
1BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL**.*16.560/0001-**RSTRES DE MAIO43218082002-01-0280478047.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.00060REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL92.816.560.0001-37LIQUIDADA
2BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL**.*16.560/0001-**RSERECHIM43070052002-01-0281048104.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.001248REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL92.816.560.0001-37LIQUIDADA
3BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL**.*16.560/0001-**RSERECHIM43070052002-01-0263046304.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.001248REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL92.816.560.0001-37LIQUIDADA
4BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL**.*16.560/0001-**RSHUMAITA43097042002-01-021500015000.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.00060REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL92.816.560.0001-37LIQUIDADA
5BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL**.*16.560/0001-**RSVERANOPOLIS43228062002-01-021500015000.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.001284REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL92.816.560.0001-37LIQUIDADA
6BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL**.*16.560/0001-**RSVERANOPOLIS43228062002-01-021000010000.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.001284REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL92.816.560.0001-37LIQUIDADA
7BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL**.*16.560/0001-**RSVERANOPOLIS43228062002-01-021500015000.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.001284REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL92.816.560.0001-37LIQUIDADA
8BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL**.*16.560/0001-**RSVISTA ALEGRE DO PRATA43236062002-01-021170011700.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.001284REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL92.816.560.0001-37LIQUIDADA
9BANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL**.*16.560/0001-**RSVISTA ALEGRE DO PRATA43236062002-01-021500015000.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.001284REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO REGIONAL DE DESENVOLVIMENTO DO EXTREMO SUL92.816.560.0001-37LIQUIDADA

Last rows

clientecpf_cnpjufmunicipiomunicipio_codigodata_da_contratacaovalor_da_operacao_em_reaisvalor_desembolsado_reaisfonte_de_recurso_desembolsoscusto_financeirojurosprazo_carencia_mesesprazo_amortizacao_mesesmodalidade_de_apoioforma_de_apoioprodutoinstrumento_financeiroinovacaoarea_operacionalsetor_cnaesubsetor_cnae_agrupadosubsetor_cnae_codigosubsetor_cnae_nomesetor_bndessubsetor_bndesporte_do_clientenatureza_do_clienteinstituicao_financeira_credenciadacnpj_do_agente_financeirosituacao_da_operacao
2083353INDUSTRIAS ROMI S A**.*20.428/0001-**SPSAO JOSE DO RIO PRETO35498052021-05-31450000450000.0RECURSOS LIVRES - FATTLP6.21345REEMBOLSÁVELINDIRETABNDES FINAMEBK AQUISIÇÃO E COMERCIALIZAÇÃONÃOAREA DE OPERACOES E CANAIS DIGITAISINDUSTRIA DE TRANSFORMAÇÃOMáquinas e equipamentosC2862300FAB MAQ EQ INDUSTRIA ALIMENTOS BEBIDAS E FUMO PECAS E ACESSORIOSINDUSTRIAMECÂNICAGRANDEPRIVADABANCO VOTORANTIM S.A.59.588.111.0001-03ATIVA
2083354J A MORAES DE LARA - LAJES**.*97.609/0001-**PRITAPERUCU41112582021-05-31100000100000.0RECURSOS LIVRES - PRÓPRIOSTAXA FIXA13.61357REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOLINHA EMPRÉSTIMO PARA MICRO E PEQUENAS EMPRESASNÃOAREA DE OPERACOES E CANAIS DIGITAISINDUSTRIA DE TRANSFORMAÇÃOMineral não metálicoC2330302FABRICACAO DE ARTEFATOS DE CIMENTO PARA USO NA CONSTRUCAOINDUSTRIAOUTRASPEQUENAPRIVADACOOPERATIVA CENTRAL DE CREDITO RURAL COM INT (01401771)01.401.771.0001-53ATIVA
2083355JULIANE POMAGERSKI 07689672957**.*68.334/0001-**PRFRANCISCO BELTRAO41084032021-05-3160006000.0RECURSOS LIVRES - PRÓPRIOSSELIC1.250120REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPROCAPCREDNÃOAREA DE OPERACOES E CANAIS DIGITAISCOMERCIO E SERVICOSAtiv financeira e seguroK6424703COOPERATIVAS DE CREDITO MUTUOCOMERCIO/SERVICOSCOMÉRCIO E SERVIÇOSMICROPRIVADACOOPERATIVA CENTRAL DE CREDITO - AILOS05.463.212.0001-29ATIVA
2083356JUSSARA FATIMA PACHECO 65098404991**.*83.609/0001-**PRCASCAVEL41048082021-05-311500015000.0RECURSOS LIVRES - PRÓPRIOSTAXA FIXA20.8939REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOLINHA EMPRÉSTIMO PARA MICRO E PEQUENAS EMPRESASNÃOAREA DE OPERACOES E CANAIS DIGITAISCOMERCIO E SERVICOSComércioG4755503COMERCIO VAREJISTA DE ARTIGOS DE CAMA, MESA E BANHOCOMERCIO/SERVICOSCOMÉRCIO E SERVIÇOSMICROPRIVADACOOPERATIVA CENTRAL DE CREDITO RURAL COM INT (01401771)01.401.771.0001-53ATIVA
2083357L DELFINO TOMAZELLI - TRANSPORTES**.*12.975/0001-**PRCASCAVEL41048082021-05-311500015000.0RECURSOS LIVRES - PRÓPRIOSTAXA FIXA20.8939REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOLINHA EMPRÉSTIMO PARA MICRO E PEQUENAS EMPRESASNÃOAREA DE OPERACOES E CANAIS DIGITAISCOMERCIO E SERVICOSTransporte terrestreH4930202TRANSP ROD CARGA EXC PROD PERIG MUDANCA INTER-MUN-EST-NACIONALINFRA-ESTRUTURATRANSPORTE RODOVIÁRIOMICROPRIVADACOOPERATIVA CENTRAL DE CREDITO RURAL COM INT (01401771)01.401.771.0001-53ATIVA
2083358LUIZ HENRIQUE PEREIRA 09189608941**.*40.920/0001-**SCTREZE DE MAIO42184002021-05-3140004000.0RECURSOS LIVRES - PRÓPRIOSTAXA FIXA9.24060REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPROCAPCREDNÃOAREA DE OPERACOES E CANAIS DIGITAISCOMERCIO E SERVICOSAtiv financeira e seguroK6424704COOPERATIVAS DE CREDITO RURALCOMERCIO/SERVICOSCOMÉRCIO E SERVIÇOSMICROPRIVADACOOPERATIVA CENTRAL DE CREDITO RURAL COM INTERACAO SOLI07.202.627.0001-74ATIVA
2083359LUMA - COMERCIO E PRODUCAO DE ARTEFATOS PLASTICOS EIREL**.*94.946/0001-**PRSAO JOSE DOS PINHAIS41255062021-05-31105130NaN-SELIC7.341248REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOLINHA EMPRÉSTIMO PARA MICRO E PEQUENAS EMPRESASNÃOAREA DE OPERACOES E CANAIS DIGITAISINDUSTRIA DE TRANSFORMAÇÃOBorracha e plásticoC2229302FABRICACAO ARTEFATOS DE MATERIAL PLASTICO PARA USOS INDUSTRIAISINDUSTRIAOUTRASMÉDIAPRIVADAAGENCIA DE FOMENTO DO PARANA S.A.03.584.906.0001-99ATIVA
2083360LUPATINI & KRAEMER LTDA**.*74.998/0001-**RSCARAZINHO43047052021-05-31400000400000.0RECURSOS LIVRES - PRÓPRIOSSELIC4.25357REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOLINHA EMPRÉSTIMO PARA MICRO E PEQUENAS EMPRESASNÃOAREA DE OPERACOES E CANAIS DIGITAISCOMERCIO E SERVICOSComércioG4665600COM ATAC MAQ E EQUIPAMENTOS PARA USO COMERCIAL, PARTES E PECASCOMERCIO/SERVICOSCOMÉRCIO E SERVIÇOSPEQUENAPRIVADABANCO BRADESCO S.A.60.746.948.0001-12ATIVA
2083361INDUSTRIAS ROMI S A**.*20.428/0001-**SPRIO DAS PEDRAS35440042021-05-31763000763000.0RECURSOS LIVRES - FATTLP6.21345REEMBOLSÁVELINDIRETABNDES FINAMEBK AQUISIÇÃO E COMERCIALIZAÇÃONÃOAREA DE OPERACOES E CANAIS DIGITAISINDUSTRIA DE TRANSFORMAÇÃOVeículo, reboque e carroceriaC2949299FAB OUTRAS PECAS ACESS P/VEIC AUTOMOTORES NAO ESPECI ANTERIORINDUSTRIAMATERIAL DE TRANSPORTEGRANDEPRIVADABANCO SANTANDER (BRASIL) S.A.90.400.888.0001-42ATIVA
2083362VLP TRANSPORTES LTDA**.*44.788/0001-**PRPARANAGUA41182042021-05-31600000NaN-SELIC7.90357REEMBOLSÁVELINDIRETABNDES FINAMEBK AQUISIÇÃO E COMERCIALIZAÇÃONÃOAREA DE OPERACOES E CANAIS DIGITAISCOMERCIO E SERVICOSTransporte terrestreH4930201TRANSP ROD CARGA EXCETO PRODUTOS PERIGOSOS E MUDANCAS, MUNICIPALINFRA-ESTRUTURATRANSPORTE RODOVIÁRIOMÉDIAPRIVADABANCO CNH INDUSTRIAL CAPITAL S.A.02.992.446.0001-75ATIVA

Duplicate rows

Most frequent

clientecpf_cnpjufmunicipiomunicipio_codigodata_da_contratacaovalor_da_operacao_em_reaisvalor_desembolsado_reaisfonte_de_recurso_desembolsoscusto_financeirojurosprazo_carencia_mesesprazo_amortizacao_mesesmodalidade_de_apoioforma_de_apoioprodutoinstrumento_financeiroinovacaoarea_operacionalsetor_cnaesubsetor_cnae_agrupadosubsetor_cnae_codigosubsetor_cnae_nomesetor_bndessubsetor_bndesporte_do_clientenatureza_do_clienteinstituicao_financeira_credenciadacnpj_do_agente_financeirosituacao_da_operacaocount
12515BANCO DO BRASIL SA**.*00.000/0001-**RSSANTA CRUZ DO SUL43168082005-06-1720002000.0RECURSOS LIVRES - TESOUROTAXA FIXA8.751224REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOMODERINFRANÃOAREA DE OPERACOES E CANAIS DIGITAISCOMERCIO E SERVICOSAtiv aux transporte e entregaH5211799DEPOSITO MERCADORIA P/TERCEIRO EXC ARMAZEM GERAL GUARDA-MOVEISINFRA-ESTRUTURAATV. AUX. TRANSPORTESMICROPRIVADABANCO DO BRASIL SA00.000.000.0001-91LIQUIDADA393
16410BANCO DO ESTADO DO RIO GRANDE DO SUL SA**.*02.067/0001-**RSHULHA NEGRA43096542002-06-2140004000.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.003660REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO DO ESTADO DO RIO GRANDE DO SUL SA92.702.067.0001-96ATIVA139
12463BANCO DO BRASIL SA**.*00.000/0001-**RSSANTA CRUZ DO SUL43168082005-05-1820002000.0RECURSOS LIVRES - TESOUROTAXA FIXA8.751224REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOMODERINFRANÃOAREA DE OPERACOES E CANAIS DIGITAISCOMERCIO E SERVICOSAtiv aux transporte e entregaH5211799DEPOSITO MERCADORIA P/TERCEIRO EXC ARMAZEM GERAL GUARDA-MOVEISINFRA-ESTRUTURAATV. AUX. TRANSPORTESMICROPRIVADABANCO DO BRASIL SA00.000.000.0001-91LIQUIDADA136
16398BANCO DO ESTADO DO RIO GRANDE DO SUL SA**.*02.067/0001-**RSHERVAL43071042002-06-2532003200.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.003660REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO DO ESTADO DO RIO GRANDE DO SUL SA92.702.067.0001-96ATIVA104
16525BANCO DO ESTADO DO RIO GRANDE DO SUL SA**.*02.067/0001-**RSJOIA43111552002-06-2140004000.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.003660REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO DO ESTADO DO RIO GRANDE DO SUL SA92.702.067.0001-96LIQUIDADA91
42037HORIZONTE EXPRESS TRANSPORTES LTDA**.*65.584/0001-**PEOLINDA26096002015-09-024223742237.0RECURSOS LIVRES - PRÓPRIOSTAXA FIXA17.64666REEMBOLSÁVELINDIRETABNDES FINAMEBK AQUISIÇÃO E COMERCIALIZAÇÃONÃOAREA DE OPERACOES E CANAIS DIGITAISCOMERCIO E SERVICOSAtiv aux transporte e entregaH5250805OPERADOR DE TRANSPORTE MULTIMODAL - OTMINFRA-ESTRUTURAATV. AUX. TRANSPORTESGRANDEPRIVADABANCO VOLKSWAGEN S.A.59.109.165.0001-49ATIVA87
42040HORIZONTE EXPRESS TRANSPORTES LTDA**.*65.584/0001-**PEOLINDA26096002015-09-027036670366.0RECURSOS LIVRES - TESOUROTAXA FIXA10.00666REEMBOLSÁVELINDIRETABNDES FINAMEPSI - BK - Ônibus e CaminhãoNÃOAREA DE OPERACOES E CANAIS DIGITAISCOMERCIO E SERVICOSAtiv aux transporte e entregaH5250805OPERADOR DE TRANSPORTE MULTIMODAL - OTMINFRA-ESTRUTURAATV. AUX. TRANSPORTESGRANDEPRIVADABANCO VOLKSWAGEN S.A.59.109.165.0001-49ATIVA87
16385BANCO DO ESTADO DO RIO GRANDE DO SUL SA**.*02.067/0001-**RSHERVAL43071042002-06-2132003200.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.003660REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO DO ESTADO DO RIO GRANDE DO SUL SA92.702.067.0001-96ATIVA80
17073BANCO DO ESTADO DO RIO GRANDE DO SUL SA**.*02.067/0001-**RSSANTANA DO LIVRAMENTO43171032002-06-2140004000.0RECURSOS VINCULADOS - FAT DEPÓSITOS ESPECIAISTAXA FIXA4.003660REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOPRONAF INVESTIMENTONÃOAREA DE OPERACOES E CANAIS DIGITAISAGROPECUÁRIA E PESCAAgropecuáriaA0100000AGRICULTURA, PECUARIA E SERVICOS RELACIONADOSAGROPECUÁRIAAGROPECUÁRIAMICROPRIVADABANCO DO ESTADO DO RIO GRANDE DO SUL SA92.702.067.0001-96ATIVA77
12566BANCO DO BRASIL SA**.*00.000/0001-**RSSANTA CRUZ DO SUL43168082005-06-3020002000.0RECURSOS LIVRES - TESOUROTAXA FIXA8.75024REEMBOLSÁVELINDIRETABNDES AUTOMÁTICOMODERINFRANÃOAREA DE OPERACOES E CANAIS DIGITAISCOMERCIO E SERVICOSAtiv aux transporte e entregaH5211799DEPOSITO MERCADORIA P/TERCEIRO EXC ARMAZEM GERAL GUARDA-MOVEISINFRA-ESTRUTURAATV. AUX. TRANSPORTESMICROPRIVADABANCO DO BRASIL SA00.000.000.0001-91LIQUIDADA68